biz_help.py

# from https://docs.streamlit.io/develop/tutorials/llms/build-conversational-apps

import streamlit as st
from langchain_upstage import ChatUpstage as Chat
from langchain_upstage import GroundednessCheck

from langchain_core.output_parsers import StrOutputParser
from langchain_core.messages import AIMessage, HumanMessage
from langchain_upstage import UpstageLayoutAnalysisLoader
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder

from langchain_groq import ChatGroq as QChat


import tempfile, os

from langchain import hub

from solar_util import initialize_solar_llm

st.set_page_config(layout="wide")
st.title("Strategic Document Generator")

# Add description and instructions
st.markdown("""
This tool generates strategic recommendations based on company information and various business documents. 
It uses both Solar Pro and Groq AI models to provide comprehensive insights.

### How to use:
1. Enter your company information in the text area below
2. Click 'Generate Strategic Document' to get AI-powered recommendations
3. View results from both models for each document analysis
""")

company_info_example = """SafeGuard Insurance Solutions is a mid-sized insurance company with over 25 years of experience in providing personal, commercial, and life insurance products. We currently serve approximately 500,000 customers across the northeastern United States.

Key Challenges:
- Manual claims processing is time-consuming and prone to errors
- Risk assessment processes need modernization to improve accuracy
- Customer service operations are overwhelmed with routine inquiries
- Fraud detection relies heavily on human analysis
- Policy underwriting takes too long, affecting customer satisfaction

Current Infrastructure:
- Legacy systems for policy management and claims processing
- Basic customer relationship management (CRM) system
- Data stored across multiple databases and systems
- Limited automation in underwriting processes

Objectives:
- Streamline claims processing through AI automation
- Enhance risk assessment accuracy using predictive analytics
- Implement AI-powered chatbots for customer service
- Strengthen fraud detection capabilities using machine learning
- Accelerate policy underwriting through intelligent automation
- Ensure compliance with insurance regulations while implementing AI solutions

We aim to transform our operations through AI integration while maintaining the personal touch our customers value.
"""

# Improve the company info input section
st.subheader("Company Information")
st.markdown("Describe your company, its challenges, and objectives.")
company_info = st.text_area(
    label="",  # Remove label since we have the subheader
    value=company_info_example,
    height=200,  # Make text area taller
    help="Include details about your company's background, current challenges, and goals."
)

# Add a divider
st.divider()

llm = initialize_solar_llm()

groq = QChat(model="llama-3.1-70b-versatile")
# https://smith.langchain.com/hub/hunkim/rag-qa-with-history
biz_help_prompt = ChatPromptTemplate.from_messages(
    [
        (
           """You are an expert business consultant with deep experience in digital transformation and AI implementation strategies. Your task is to analyze the provided document and company information to generate actionable strategic recommendations.

Please follow these guidelines:
1. Match your response language to the company information's language (English for English, Korean for Korean, etc.)
2. Focus on practical, implementable solutions that align with the company's:
   - Current challenges and pain points
   - Infrastructure and technical capabilities
   - Stated objectives and goals
   - Industry context and regulations

3. Structure your response with:
   - Executive Summary (2-3 key points)
   - Strategic Recommendations (prioritized by impact and feasibility)
   - Implementation Timeline (short-term, medium-term, long-term)
   - Expected Outcomes and KPIs
   - Potential Risks and Mitigation Strategies

4. Ensure recommendations are:
   - Specific and actionable
   - Cost-effective and scalable
   - Aligned with industry best practices
   - Supported by relevant examples from the document

----
Document:
{doc}
----
Company Information:
{company_info}

Match your response language to the company information's language (English for English, Korean for Korean, etc.)
Generate a strategic analysis and recommendations that will help this company achieve their objectives."""
  
        )
    ]
)

groundedness_check = GroundednessCheck()


def get_response(document_content, company_info):
    chain = biz_help_prompt | llm | StrOutputParser()

    return chain.stream(
        {
            "doc": document_content,
            "company_info": company_info,
        }
    )

def get_response_groq(document_content, company_info):
    chain = biz_help_prompt | groq | StrOutputParser()

    return chain.stream(
        {
            "doc": document_content,
            "company_info": company_info,
        }
    )


documents = [
    {
        "name": "Go To Market – US Launch Prioritization Exercise",
        "content": """
     Overview
•	This is a conversational assessment and prioritization exercise with Upstage AI. We're excited about the amazing opportunities that Upstage AI has to look forward to, pending execution and development.
•	Basic overview of US Launch components for Upstage AI across the next 30-60-90-180. Considering the early stage of Upstage AI in the US Market, most items (ie: Channel Development et al. will be 2025 initiatives).
•	These are general thoughts that need to be prioritized and customized with Upstage AI leadership
•	Additional considerations need to be added
•	Granular process outlines are addressed via separate cover

Baseline Q&A
Prioritization Exercise with Upstage AI Leadership:
1.	Define Top Line Sales Targets – or – new Customer Acquisition Targets for the US Market
a.	Existing Customer Data:
•	Number of customers
•	Revenue per customer
•	Sales cycle?
•	Geographic distribution?
•	By Product / Solution
•	How many named/branded solutions do you have?
b.	Using APJ numbers for reference, calculate historical initial revenue per sale (which will aggressively scale as we build this out and progress).
c.	What is your target revenue in the US Market for years 1,2,3?
d.	Work backwards from the number and define the quantity of new opportunities needed
e.	Average across quarter and month to establish monthly targets
f.	As this is a net-new early-stage geography, that is currently understaffed estimates will need to be conservative. 
g.	Is your goal build / hold, to be acquired, or to go public? Timelines?

2.	Company Headcount (by geo)
a.	Customer Facing: Sales & Sales Engineering
b.	Solution Implementation Post Sales and ongoing Customer Success / Expansion
c.	Customer Service
d.	Back End Developers
e.	Technical Support
f.	Senior Leadership
g.	Do you offer Services? Implementation, Foundation Model Training, Fine Tuning? Ongoing MSP?
h.	Subscription based Managed Services (MSP)? Let's discuss and a GenAI MSP business as a key opportunity for ARR and Industry Leadership opportunities. 

3.	Capacity Assessment: Opportunity & Customer Load
a.	How much time does it take to launch a new customer by solution?
b.	In your estimation, what is your biggest business and organizational constraint that headcount is needed for? What is the primary driver of new head count needs?
c.	How many headcount are you projecting for the US Market?
d.	What is your staff utilization rate of technical resources? (Percentage of billable time?)
e.	Current customer commitment work backlog? (New deals, ongoing support, new features et al.).
f.	US specific to current staffing in place:
•	How many of the following can you concurrently manage today?
•	Customers (customer success, customer service and tech support)
•	Open Opportunities?
•	New Implementations?
g.	NEXT STEP: Compare topline revenue and customer targets + HC targets to these numbers? Work backwards to find the balance.

4.	Clearly Defined Product & Revenue Streams
a.	Current solutions on AWS: OCR, LM, ASKUP.
b.	Are you familiar with the OCR marketplace in the US? Have you assessed it? What specific solutions are you looking to drive in the US market for Day #1 GTM?
c.	What do you envision as your product market fit in the US?
d.	NOTE: Best play in US may be foundationally, and finely tuned Language Models, bundled with services and discreet product sets? Example: Diagnostic Healthcare LM that factors all key data points, patient profile, tests/labs and patient symptom? Incumbents like OpenAI and Anthropic et al, are NOT doing this.
e.	Do you envision selling both models and industry/trained/fine-tuned solutions?
f.	How do you calculate go to market pricing? How do you reassess and refine? Are you indexing on margin, volume or seeking a balance? 
g.	What are your: 1) Product lines? 2) Products (ie: one off?) 3) Service offered?
h.	How do you price your products and solutions today? Clear Pricing & Packaging for all products?
i.	How does recurring revenue (ARR) work? What percentage of your revenue is ARR versus 1 time transactions? 
j.	Note: TPM / Tokens are confusing to customers. Customer friendly verbiage has to be used.
k.	If a model is implemented in the customer's environment how do monetize/charge for it.
l.	Products listed by name with clear, concise data, benefits, features, use cases, pricing and competitive comparisons?
m.	How much customization is needed for each sale? Can a customer buy a product off the shelf and have it work?
n.	How do customers transact with you today? How many touches are needed? How is payment remitted? What types of payment?
o.	What contracts and agreements are in place between the customer and Upstage?
p.	Public Sector Contract Vehicles in place?
q.	What is your margin on a per product basis?
r.	Do you have any analysis on the number of person hours needed to implement?
s.	Existing Industry Solutions?
t.	How do you want to be defined as a company? Product company? SaaS? Consulting? Both?

5.	Fully define Internal & External Processes and talk tracks as outlined via separate cover
a.	End to End Sales Process must be built before engaging with customers at scale. 
b.	Outlines via separate cover

6.	Define internal capacity and bottlenecks:
a.	How many leads can you currently handle?
b.	How many concurrent sales opportunities can your US Team support?
•	Pre-Sales Support? Sales + Technical Headcount in place?
•	Proof of Concept & Solution Design -> Implementation?
•	Post-Sale Customer Support and Service?

7.	CRM Sales Stages & Process defined

8.	Ability to transact in the US? Commercial Sector & Public Sector considerations.

9.	Refine Value Proposition and Market Positioning
a.	Clarify Core Differentiators:
•	Why AI? Why Upstage?
•	Emphasize Upstage AI's cost efficiency, domain-specific models, and ease of integration. Highlight how these advantages directly address key challenges faced by target US industries (e.g., data privacy concerns in healthcare, cost optimization in finance).
•	Position Upstage AI as a "value-driven AI solution" that offers high performance with lower infrastructure costs, differentiating it from established competitors like OpenAI and Anthropic.

10.	Create Clear Customer Segmentation:
a.	Prioritize industries where Upstage AI has already demonstrated success, such as healthcare and finance etc. 
b.	Develop targeted messaging for each segment, focusing on proven outcomes (e.g., 18% reduction in hospital readmissions, 20% increase in e-commerce sales conversions).
c.	Social Proof: Polished, data driven customer success stories from other geographies, mapped by industry and use case. Must in English.


11.	Develop a Focused Go-to-Market Plan
a.	Preparation and Alignment:
•	Build / at minimum define, a core US entry team, including experts in AI, marketing, sales, and customer success. 
•	Recruit industry-specific sales leadership along with core consultants. This will take 1 – 2 quarters. 
•	Review market segments that are adjacent to existing strengths – determine low lift solution design and go to market.
•	Launch Account-Based Marketing (ABM) initiatives targeting decision-makers at Fortune 500 companies within these verticals, using data-driven insights to personalize outreach.
•	Review Lead Generation Outline document via separate cover.

b.	Lead Development Execution and Quick Wins:
•	Initiate direct outreach campaigns using tailored pitches backed by data and case studies (e.g., Samsung and Hanwha success stories).
•	Deploy content marketing and social selling strategies on LinkedIn and other platforms to establish thought leadership and generate inbound leads.
•	Activate partnerships with key resellers, VARs, and OEMs; offer co-branded solutions and develop joint marketing campaigns.
•	See Lead Generation document via separate cover.
•	SEO optimized for each industry and solution set. Engage with 3rd Party.

c.	Optimization and Early Growth:
•	Assess and refine sales and marketing strategies based on data analytics. Focus on high-performing channels and pivot where necessary.
•	Establish an Upstage User Community to foster engagement, provide feedback, and create brand advocates.
•	Begin planning for major industry events and conferences to expand visibility and network with key stakeholders.

12.	Leverage Strategic Partnerships and Alliances
a.	Form High-Impact Partnerships:
•	Partner with SaaS providers and enterprise software companies to integrate Upstage AI capabilities into existing platforms. Utilize the "Powered by Upstage AI" branding to quickly build credibility.
•	Engage with managed service providers (MSPs) and systems integrators specializing in healthcare, finance, and education to bundle Upstage AI within their service offerings.
•	Collaborate with cloud providers for marketplace listings and co-sell opportunities.

13.	Develop a Tiered Reseller Program:
a.	Create structured reseller tiers with escalating benefits 
b.	Implement a performance-based incentive program to motivate partners and drive sales growth.

14.	Build Brand Authority through Thought Leadership and Content
a.	Publish high-quality content such as whitepapers, e-books, and blogs that address industry-specific challenges and position Upstage AI as an expert in generative AI.
b.	Utilize key executives and sales leaders to share insights and success stories on LinkedIn and in industry forums.

15.	Participate in Industry Events and Webinars:
a.	Host virtual events and webinars focused on Upstage AI's unique capabilities and industry-specific applications.
b.	Attend and present at major industry events like CES, TechCrunch Disrupt, and AI Summit to build visibility and establish relationships with potential clients and partners.

16.	Execute a Robust Freemium Strategy
a.	Launch a Free Tier to Drive Adoption:
•	Provide a robust free tier with valuable features to attract startups and SMBs, using it as a pipeline for upselling premium services.
•	Leverage analytics to identify high-potential free users and deploy targeted upselling campaigns.

17.	Offer High-Value Educational Content:
a.	Create online courses, webinars, and certifications that demonstrate how to maximize Upstage AI's capabilities, encouraging deeper engagement and loyalty.
b.	Multiple Libraries residing on your web site, in addition to a membership area should be addressed:
•	Public facing: Demos, Seminars, Value Props, 

18.	Optimize Product Offering and Customer Experience
a.	Enhance Product Based on Feedback:
•	Actively gather customer feedback to refine products and services; implement an agile development approach for continuous improvement.
•	Prioritize adding features that address specific pain points in key verticals.
•	The platform, and the web site should have customer suggestions baked into each page. Opportunity: provide recognition to customers that make the most suggestions / highest quality suggestions that are adopted.

19.	Expand Globally with a Localized Approach
a.	Target International Markets:
•	Research and enter markets with high AI adoption potential (e.g., Europe, APAC). Localize products and marketing strategies to align with regional regulations and cultural nuances.
•	Focus on partnerships with local resellers and distributors to navigate regulatory landscapes and build trust.

20.	Implement Data-Driven Measurement and Optimization
a.	Set Clear KPIs and Metrics:
•	Define KPIs for lead generation, conversion rates, customer acquisition cost, customer lifetime value, and market penetration.
•	Regularly review performance data and conduct A/B testing to optimize messaging, campaigns, and product offerings.

21.	Adapt and Evolve Based on Market Feedback:
a.	Use real-time data to quickly adapt strategies, focusing on what drives the most value and eliminating low-impact activities.

""",
    },
    {
        "name": "Sales Process Outline",
        "content": """Purpose: 
•	Provide a longitudinal outline of the optimal direct sales process from lead through post-sales.
•	Greater detail for each step is addressed via separate cover.
•	Note: this document assumes that a CRM with clearly established sales stages, best practices, and forecasting process is in place. 
Sales Process Definition and Importance for Upstage AI:
•	Defined: A systematic series of steps a sales team follows to identify, qualify, and convert potential customers into paying clients, extending through Customer Success & Lifecyle.
•	Importance:
o	Efficiency: Streamlines employee on-boarding and sales activities, reducing wasted time and effort.
o	Consistency: Ensures a standardized approach, improving customer experiences and drives company culture, along with commonality. Assists with succession planning, growth and employee attrition. 
o	Predictability: Provides a framework for forecasting sales and revenue.
o	Accountability: Defines clear roles and responsibilities within the sales team.
o	Scalability: Supports growth by enabling repeatable processes, and allows leadership to collaborate with top performers in capturing emerging best practices.
o	Reduces: Sales cycles, customer & employee ambiguity, while increasing pipeline velocity and closing percentages. Also reduces customer acquisition costs.
o	Increases: Number of opportunities generated on a per meeting, per customer bases; Overall Opportunity value and customer value.
o	Valuation: Having a documented, refined set of repeatable processes increases company valuation at time of exit. Acquisitions are enhanced when strong succession planning and repeatable processes are foundational components are already in place. 
o	Removes: Dependence on individual leaders and contributors
Required Processes to be developed:
•	Direct Sales Process
•	Channel / Reseller On-Boarding, Training, Development and Co-Sell Processes
•	Customer Success Process
•	Sales Engineering & Solution Design
•	Vertical / Industry Customization

Lead Generation Ideation - Outline
1.	Lead generation Sourcing
a.	Target: existing areas of industry expertise that builds off of existing, successful customer case studies (data driven) and testimonials. Create tailored pitches that highlight how Upstage AI's unique features (cost efficiency, domain-specific APIs, and ease of integration) address specific industry pain points.
b.	Direct sales / marketing outreach using Account-Based Marketing to identify and engage with high-value prospects. Use data-driven insights to personalize outreach and demonstrate a deep understanding of each potential client's unique challenges, that Upstage AI can address.
c.	Website (drive traffic to landing pages with clear value propositions and rich media demonstrations)
d.	Customer Referral Program 
e.	Marketing via LinkedIn, Facebook, Trade and Industry 
f.	Newsletters, blogs, social media, Customer Referral Program
g.	Channel
h.	Co-Sell with trusted cloud and channel partners where possible. Leverage their marketplaces, and co-branded solutions if possible. 
i.	Upstage User Community? Upstage Marketplace? (Discuss potential for a model marketplace)
j.	Free / Freemium Users: Provide as much value for the free tier, combined with no cost on-demand training. Profile this user base, drive social media and direct email marketing for upsell

Example Customer Facing Direct Sales Process Outline for Upstage

1.	Value Proposition / Customized Benefit & Feature Statements
a.	General, multi-faceted statements 
b.	Targeted persona, buyer type and industry
c.	Varying Length: 15-20 seconds through 60-90 seconds.

2.	Customer Facing Discovery Process / Comprehensive Needs Analysis

3.	Comprehensive Customer Presentation & Solutions Discussion tied to customer needs and key recommendations identified during the Discovery & Pre-Call Planning Process:
a.	Power Point / Online Demo / Pre-Recorded Segments also available online
i.	Comprehensive Benefit & Feature Presentation that allows sales to address overt customer interest, but also provide a comprehensive overview of the company, industry and 'challenges' faced by customers and the art of the possible.

4.	Post-Presentation Processes aligned to this process
a.	Setting the next series of meetings, with clear dates, roles & responsibilities, outcome objectives – linked to a clear, urgent WHY that works backwards from a clear deadline. 
b.	Proof of concept process
c.	Solution Design / Defining Scope of Work (if applicable) / Presenting Price and Terms (where applicable).
d.	Implementation Planning / Strategy / Execution – end to end process
e.	Capture / Procurement for both PS and CS Customers

5.	Customer Lifecycle
a.	Quarterly Customer Review Meetings that assess: satisfaction, questions, areas of need, customer service, customer feedback and ideation for new products/services, additional areas of opportunity for growth and expansion (cross – sell – upsell) all linked back to the original needs analysis, which should be a living document that's updated. All records, notes must be saved in Salesforce.com.

6.	Internal Processes
a.	Forecasting & Opportunity Review Process & Rubrics (internal)
b.	Internal Sales Process Playbooks and example templates
c.	Employee Check Ride & Training
d.	Sales & Sales Engineer Engagement Process (sales should be supported by sales engineering early and often)

(Additional processes as noted above to be added below)""",
    },
    {
        "name": "Lead Generation Ideation Outline",
        "content": """
Overview
•	Basic overview of US GTM & Lead Generation Strategies for Upstage AI across the next 30-60-90
•	These are general thoughts that need to be prioritized and customized with Upstage AI leadership
•	Additional considerations need to be added
•	Granular process outliens are addressed via separate cover

1.	Leverage Existing Expertise and Success Stories
o	Tailored Pitches Using Case Studies:
	Utilize successful customer case studies and testimonials to create personalized pitches.
	Highlight Upstage AI's unique features like cost efficiency, domain-specific APIs, and ease of integration.
	Address specific industry pain points by showing real-world solutions.
o	Develop Industry-Specific Content:
	Create whitepapers, e-books, and blog posts that delve into industry challenges.
	Position Upstage AI as a thought leader by providing valuable insights and solutions.
2.	Direct Sales and Marketing Outreach
o	Account-Based Marketing (ABM):
	Implement ABM to identify and engage high-value prospects.
	Personalize outreach with data-driven insights that showcase how Upstage AI meets their specific needs.
o	Hire and Train Local Sales Teams:
	Establish small team of tenures sales consultants 
	Recruit professionals experienced in selling AI and cloud-based solutions to mid-sized and enterprise clients.
o	Focus on High-Growth Industries:
	Target sectors with high AI demand such as healthcare, finance, retail, and manufacturing.
	Craft tailored pitches that highlight Upstage AI's value propositions for each industry.
o	Leverage Success Stories:
	Use existing case studies with clients like Samsung and Hanwha to build credibility.
	Demonstrate tangible results and ROI to potential clients.
3.	Website Optimization and Digital Presence
o	Enhance Landing Pages:
	Optimize landing pages with clear value propositions and compelling calls-to-action.
	Incorporate rich media demonstrations to showcase product capabilities.
o	Improve SEO and Content Strategy:
	Implement SEO best practices to drive organic traffic.
	Regularly publish high-quality content addressing industry challenges and solutions.
4.	Customer Referral Program
o	Incentivize Referrals:
	Encourage existing customers to refer new prospects through rewards or discounts.
	Offer benefits to both the referrer and the new customer to motivate participation.
o	Create Exclusive Offers:
	Provide early access to new features or premium support for customers who refer others.
5.	Multi-Channel Marketing
o	Utilize Social Media Platforms:
	Engage audiences on LinkedIn, Facebook, Twitter, and industry-specific forums.
	Share thought leadership content, company updates, and success stories.
o	Email Marketing Campaigns:
	Develop targeted email campaigns to nurture leads and keep clients informed.
o	Content Syndication:
	Publish articles and blogs on third-party platforms to expand reach.
6.	Channel Partnerships and Collaborations
o	Collaborate with Resellers and Integrators:
	Partner with resellers, ISVs, and system integrators specializing in key industries.
	Provide training and marketing materials to enable them to effectively sell Upstage AI solutions.
	Collaborate with resellers, ISVs, MSPs, developer communities, and higher education institutions. Provide training, marketing materials, and incentives to promote Upstage AI solutions.
	Partner with value-added resellers (VARs) and system integrators specializing in verticals like healthcare or finance to offer Upstage AI in broader service offerings.
	Create a structured reseller program with tiered benefits (discounts, co-marketing funds, dedicated account managers) and a performance-based incentive program.
o	Engage with Developer Communities and Academia:
	Work with developer communities and higher education institutions to promote adoption.
	Offer workshops, webinars, and collaborative projects.
7.	OEM Partnerships and White-Label Opportunities
o	Form OEM Partnerships:
	Partner with SaaS companies and enterprise software providers to integrate Upstage AI into their products.
	Use co-branding opportunities like "Powered by Upstage AI" to increase visibility.
	Target OEM relationships in key verticals (healthcare, finance, education) to add value with domain-specific models.
o	Offer White-Label Solutions:
	Provide white-label versions for companies wanting to add AI capabilities without developing their own.
	Customize solutions to fit partner branding and requirements.
o	Target Key Verticals:
	Focus on industries like healthcare, finance, and education for OEM relationships.
	Leverage domain-specific models to add significant value.
8.	Co-Selling Initiatives
o	Collaborate with Cloud and Channel Partners:
	Engage in co-selling efforts with trusted partners.
	Leverage their marketplaces and co-branded solutions to reach a wider audience.
o	Joint Marketing Efforts:
	Participate in joint webinars, workshops, and events to showcase combined expertise.
9.	Community and Marketplace Development
o	Develop an Upstage User Community:
	Create forums or online communities for users to share experiences and best practices.
	Host regular Q&A sessions and webinars to engage with the community.
o	Explore a Model Marketplace:
	Establish a marketplace for AI models where developers can share and access resources.
	Encourage innovation and collaboration within the ecosystem.
10.	Free/Freemium Strategy
o	Offer a Robust Free Tier:
	Provide valuable features and training resources in a free tier to attract new users.
	Use the free offering as a gateway to upsell premium services.
o	Targeted Upselling Campaigns:
	Use data analytics to identify potential upsell opportunities.
	Highlight advanced features and benefits to convert free users to paid plans.
Sales Strategies
1.	Direct Sales
o	Local Sales Teams with Industry Expertise:
	Build teams with knowledge in specific industries to provide tailored solutions.
	Offer personalized demos and consultations.
o	Strategic Account Management:
	Assign dedicated account managers to high-value clients.
	Foster long-term relationships and identify opportunities for expansion.
2.	Channel Sales
o	Expand Through Strategic Partnerships:
	Collaborate with VARs and system integrators to penetrate new markets.
o	Cloud Marketplace Listings:
	List Upstage AI solutions on AWS, Azure, and Google Cloud marketplaces.
	Leverage their customer base for increased exposure.
3.	Reseller Program
o	Structured Reseller Tiers:
	Create tiers with escalating benefits (TBD)
o	Comprehensive Training and Support:
	Provide resellers with the necessary tools and knowledge to succeed.
o	Incentive Programs:
	Offer performance-based rewards to motivate and retain top-performing resellers.
Marketing and Brand Building
1.	Social Selling and Thought Leadership
o	Leverage LinkedIn:
	Encourage executives and sales leaders to share valuable content and engage with prospects.
	Participate in relevant groups and discussions.
o	Engage on Community Platforms:
	Actively participate in discussions on Twitter, Reddit, and industry forums.
	Share insights and answer questions to build trust.
2.	Influencer and Partner Marketing
o	Collaborate with Industry Influencers:
	Partner with thought leaders for endorsements and co-created content.
	Use their platforms to reach a broader audience.
o	Customer Advocacy Programs:
	Highlight satisfied customers as brand ambassadors in marketing efforts.
3.	Events and Conferences
o	Host Virtual Events and Webinars:
	Organize events focused on solving industry challenges with Upstage AI.
	Provide actionable insights and live demonstrations.
o	Participate in Industry Conferences:
	Attend and present at major events like CES and TechCrunch Disrupt.
	Network with potential clients and partners.
4.	Localized Marketing and Messaging
o	Tailor Campaigns to the US Market:
	Emphasize local success stories and address region-specific challenges.
	Adapt messaging to resonate with cultural and industry nuances.
Product and Service Enhancements
1.	Managed Services
o	Develop Managed AI Service Packages:
	Offer comprehensive services including deployment, customization, and maintenance.
	Target clients lacking in-house AI expertise.
o	Bundle Services with MSPs:
	Partner with managed service providers to include Upstage AI in their offerings.
o	Premium Customer Support:
	Provide options for dedicated support teams, faster response times, and personalized assistance.
2.	Continuous Innovation
o	Invest in R&D:
	Stay ahead by continually improving products and adding new features.
o	Customer Feedback Integration:
	Actively seek and incorporate customer feedback into product development.
Additional Strategies
1.	Customer Success Stories
o	Develop Detailed Case Studies:
	Highlight challenges, solutions, and measurable outcomes.
	Use storytelling to make the content engaging and relatable.
o	Video Testimonials:
	Create short videos featuring customer experiences and success.
2.	Educational Content and Training
o	Offer Training Programs:
	Provide workshops, certifications, and online courses.
	Help customers maximize the value of Upstage AI solutions.
o	Resource Library:
	Maintain a library of guides, FAQs, and best practices.
3.	Feedback and Improvement
o	Implement Feedback Mechanisms:
	Use surveys, user forums, and direct outreach to gather input.
o	Regular Updates:
	Keep clients informed about improvements and how they address their needs.
Expansion Opportunities
1.	International Markets
o	Assess Global Expansion:
	Research and identify markets with high AI adoption potential.
	Localize products and marketing strategies for cultural relevance.
o	Compliance and Regulations:
	Ensure products meet international standards and legal requirements.
2.	Industry Vertical Solutions
o	Develop Specialized Offerings:
	Create solutions tailored to specific industries with unique needs.
	Address compliance, data security, and domain-specific challenges.
3.	Academic and Research Partnerships
o	Collaborate with Educational Institutions:
	Partner on research projects and innovations.
	Offer internships and support for AI curriculum development.
o	Sponsor Hackathons and Competitions:
	Engage the developer community and identify emerging talent.
Community Engagement and Development
1.	Build a Developer Ecosystem
o	API Access and Documentation:
	Provide comprehensive documentation and easy access to APIs.
	Encourage developers to build applications on top of Upstage AI.
o	Developer Support Programs:
	Offer forums, support channels, and troubleshooting guides.
2.	Open Source Contributions
o	Participate in Open Source Projects:
	Contribute to the community and enhance brand reputation.
o	Host Open Source Initiatives:
	Encourage collaboration and innovation by sharing select resources.
Customer Retention and Loyalty
1.	Personalized Customer Engagement
o	Regular Check-Ins:
	Schedule periodic meetings to assess satisfaction and needs.
o	Customized Solutions:
	Offer tailored services based on client feedback and usage patterns.
2.	Loyalty Programs
o	Reward Long-Term Clients:
	Provide discounts, early access to new features, or exclusive content.
o	Client Advisory Boards:
	Involve key customers in product development discussions.
Measurement and Optimization
1.	Data-Driven Decision Making
o	Analytics and Reporting:
	Use analytics to measure the effectiveness of marketing campaigns and sales strategies.
o	Key Performance Indicators (KPIs):
	Establish KPIs for lead generation, conversion rates, customer acquisition cost, and customer lifetime value.
2.	Continuous Improvement
o	A/B Testing:
	Experiment with different marketing messages, channels, and strategies.
o	Performance Reviews:
	Regularly assess sales and marketing efforts to identify areas for improvement.

        """,
    }, {
        "name": "Messaging & Value Proposition Ideation",
        "content": """
Crafting Effective Messaging & Benefit Statements
1. Value of Clear, Concise Benefit Statements
•	Why They Matter:
o	People care about how you're relevant to their needs, goals, and objectives. Everyone's tuned into WIIFM.com: "What's in it for me?" We need to answer this internal question within 10-15 seconds to earn their attention for further discussion.
o	Benefit statements translate features into customer value, helping them see how your product solves their specific problems. They help customers visualize the benefits they'll receive from what you offer, breaking through preoccupation and grabbing their attention.
o	They position you as a potential subject matter expert—someone worth meeting.
o	You should maintain a repository of well-crafted statements for all buyer personas and industry-specific solutions you offer, including longer, balanced statements that cover all buyer types. Use these based on the situation: press releases, media engagements, presentations, elevator pitches, industry events.
o	Lacking crisp, relevant, and attractive statements for all buyer personas and applicable industry use cases puts you at an immediate disadvantage and can lead to potential failure.
•	Differentiate Between Features and Benefits:
o	Feature: A factual statement about a product (e.g., "Solar LLM can run on a single GPU").
o	Benefit: What the feature means to the customer (e.g., "Reduces your hardware costs while delivering high performance, all while keeping it secure in your own environment").
o	Key Point: Few people buy based on features alone; they seek solutions that meet their needs and objectives. People are looking for solutions to their problems.
o	Avoid Feature Dumps: Steer clear of this approach as it detracts value and commoditizes your offering.
2. Step-by-Step Guide to Crafting Benefit Statements
•	Step 1: Key Non-Negotiables
o	Use quantifiable data whenever possible. Contrast to norms, competition, common challenges, and problems all customers face. Be brief, clear, and concise.
o	Be prepared to "stack" benefit statements in succession. Provide relevant Statement #1, ask an open-ended question about their challenges or goals, and follow up conversationally with additional statements that align with their response or add more contextual benefits. This dialogue opens up a functional needs analysis.
•	Step 2: Understand & Define Customer Pain Points
o	Identify the challenges and limitations customers face in solving their problems with current solutions and providers—be as specific as possible. Ask yourself:
	What challenges do our customers face that Upstage AI's features and solutions address?
	If I were in my customer's shoes, how would I feel about the GenAI space? What would confuse me in selecting a GenAI solution?
	What risks are my customers or prospects facing? How will we preemptively address those concerns?
	What's the state of today's GenAI marketplace? Is there ambiguity? What are the biggest concerns—pricing, resource requirements, security, privacy?
	How does Upstage AI solve these issues and more?
•	Step 3: Identify Key Features & Benefits of Upstage AI
o	List the core features of Upstage AI products and solutions, both broadly and for specific industries.
•	Step 4: Formulate 30-40 Benefit Statements
o	Use a formula: Feature + What It Does + Why It Matters + Data (if possible). For example, "The Solar LLM runs efficiently on a single GPU, lowering operational costs while maintaining high processing speed."
o	Review, edit, and combine different pieces to create compelling, multi-layered value propositions that cover multiple bases.
o	Continuously refine, role-play with your team, and document them in an iterative database on a shared drive.
o	Note: A comprehensive list of starting points is provided at the end of this document.
3. Interactive Workshop Activity: Crafting Benefit Statements (If Time Permits)
•	Group Exercise:
o	Divide leadership into small teams. Provide a list of features and have them craft benefit statements based on identified customer needs.
•	Review and Feedback:
o	Each group presents their benefit statements. Facilitate a discussion on which statements are most compelling and why.
•	Refinement Session:
o	Encourage teams to refine their statements based on feedback, focusing on clarity, customer-centric language, and alignment with known customer needs.
4. Final Wrap-Up
•	Discuss Key Takeaways:
o	Emphasize the importance of using customer insights to craft compelling benefit statements.
•	Next Steps:
o	Set a deadline for creating your general, technical, non-technical, and industry-specific feature and benefit statements.
o	Schedule time for iteration and modification.
Example Benefit Statements – Features & Benefits 
Ideation & Reference
Note: 
1.	Upstage AI specific example statements, and verbiage sets – as starting points - are provided in the sections below.
2.	It's important to naturally paraphrase where appropriate, and to 'make it your own' to insure natural conversational flow and expression. 

Comprehensive F&B Statement Examples
1.	Examples
o	We're a global GenAI company that saves customers between 20% to 50% in operational costs versus other solutions while giving our customers a massive 250% increase in performance versus other models. If security is important to you, we can also deploy directly into your environment, which reduces complexity, ensures the security of your data and saves you even more money.
o	We provide 12 customizable products that save customers between 20% to 50% in operational costs versus other models, while improving performance by up to 10% versus other models like GPT-4. By leveraging solutions such as Solar LLM, which leads the Hugging Face Open LLM Leaderboard, and domain-specific tools for healthcare, finance, education, legal, and e-commerce, Upstage AI democratizes generative AI with flexible on-premise and API offerings. Our models enable a 2.5x faster response rate, reduce patient readmissions by 18%, and boost e-commerce sales by 20%, providing scalable, cost-effective, and secure AI solutions across every key industry vertical, ensuring both local and global support.

2.	Upstage Delivers Cost-Efficient and Secure AI Solutions
o	Upstage reduces hardware costs by up to 50% with the Solar LLM, which operates efficiently on a single GPU and eliminates cloud fees with secure on-premise deployment. Automate tasks like document processing and content creation, freeing your team for strategic work while ensuring data privacy. Trusted by leaders like Samsung and Hanwha, Upstage AI's scalable solutions deliver high performance across sectors, from healthcare to finance, providing consistent value as your business grows.
3.	Upstage Transforms Industries with Tailored AI Solutions
o	Upstage AI enables healthcare providers to reduce patient readmission rates by 18% and boosts e-commerce sales conversions by 20% through AI-driven personalization. It delivers industry-specific solutions that outperform generalist models, enhancing risk assessment in finance, streamlining operations, and ensuring compliance—all while prioritizing data security and multilingual support.

Non-Technical Buyer Benefit Statements
1.	Cost-Efficient AI Without Heavy Investment
o	Upstage AI's Solar LLM cuts hardware costs by up to 50% compared to other models, by running efficiently on a single GPU, rather than full racks of servers, like our competition. Our optional on-premise approach also eliminates cloud subscription fees, offering a more affordable way to access advanced AI capabilities. 
o	Our on-premise approach eliminates cloud subscription fees – and removed API complexity, cost and data security risk - making generative AI solutions more affordable for your business.
2.	Faster Results with Less Complexity
o	Deploy Upstage AI in days, not months. Our ready-to-use AI tools integrate smoothly into your existing workflows, providing rapid returns on your investment.
3.	Tailored AI for Your Industry Needs
o	Whether you're in healthcare, finance, retail or other key industries, Upstage AI offers specialized APIs designed for your unique challenges, ensuring higher accuracy and relevance in your operations.
4.	Boost Efficiency with Automation
o	Automate time-consuming tasks with Upstage AI's powerful document processing and natural language tools, freeing your team to focus on what matters most.
o	Unlock the power of AI content creation without compromising data security. Generate marketing copy, product descriptions, and more—all on your own infrastructure.
o	Secure on-premise deployment ensures your data remains private and compliant, ideal for highly regulated industries.
5.	Data Privacy You Can Trust
o	With options for on-premise deployment and advanced data encryption, Upstage AI ensures your sensitive information stays secure, meeting all compliance needs.
6.	Flexible Pricing for Maximum Value
o	Upstage allows you to start small, with flexible pricing plans. Explore AI solutions tailored to your business size and growth stage with options like a free tier, paying only for what you need.
7.	AI That Grows with Your Business
o	Upstage AI's scalable solutions adapt to your growth, from small pilot projects to full-scale AI deployments, providing value at every stage of your journey.
8.	Simplified AI Adoption
o	Our user-friendly interfaces and comprehensive support make AI accessible for everyone on your team, eliminating the need for deep technical expertise.
9.	Proven Performance Across Industries
o	Trusted by leaders like Samsung and Hanwha, Upstage AI delivers powerful, reliable AI solutions that enhance productivity and streamline operations.
10.	Accelerate Your Digital Transformation
o	Jumpstart your digital transformation with Upstage AI's fast, effective tools designed to deliver immediate impact on your bottom line.
11.	Cost-Effective and Efficient AI Solutions
o	Our Solar Mini models provide responses 2.5 times faster than GPT-3.5 while offering significant cost savings, and giving you comparable performance, reducing computational time and costs.
o	This efficiency translates to significant cost savings for your business, making Upstage AI an economical choice without compromising performance.
Technical Buyer Benefit Statements
1.	Optimize AI with Minimal Hardware
o	Upstage AI's Solar LLM cuts hardware costs by up to 50% compared to other models, by running efficiently on a single GPU, rather than full racks of servers, like our competition. Our optional on-premise approach also eliminates cloud subscription fees, offering a more affordable way to access advanced AI capabilities. 
o	Rather than bringing your data to the model, we empower you to bring THE MODEL to your DATA! This cuts costs, eliminated API issues and complexity, removes data egress concerns, and also keeps YOUR DATA SECURELY within your environment!
o	Upstage AI's Solar LLM delivers high performance on a single GPU, reducing hardware needs by up to 60% while ensuring data security and accuracy.
o	Upstage AI's Solar LLM delivers high-performance AI capabilities on a single GPU, reducing hardware requirements and operational costs without compromising speed or accuracy.
o	Our models can run locally, ensuring data security and preventing data leaks, with a focus on mitigating AI hallucinations. This emphasis on security makes Upstage AI ideal for industries handling sensitive information like finance and healthcare.
2.	Advanced AI with Simplified Integration
o	Easily integrate Upstage AI tools with your existing systems using our robust APIs, ensuring seamless adoption and minimal disruption to your current tech stack.
3.	Customizable AI for Specific Domains
o	Upstage AI offers domain-specific APIs for healthcare, finance, and legal sectors. Leverage purpose-built models that outperform generalist AI solutions for higher precision in your applications.
4.	Lightning-Fast Deployment
o	Deploy state-of-the-art AI models quickly with our streamlined installation process, getting your systems up and running faster than with traditional AI providers.
5.	Efficiency Through Depth-Up Scaling
o	Benefit from Upstage AI's unique Depth-Up Scaling technique, maximizing computational efficiency to deliver superior performance at a lower operational cost.
6.	Enhanced Security and Compliance
o	With on-premise deployment options and robust encryption, Upstage AI helps you maintain full control over your data, ensuring compliance with stringent regulatory standards.
o	Our focus on security prioritizes data privacy, offering a reliable solution for industries that handle sensitive information.
7.	Extensive Developer Support and Tools
o	Leverage comprehensive tutorials, detailed documentation, and a developer-friendly playground to quickly build, test, and deploy AI models that meet your unique requirements.
8.	Flexible API Integration Across Platforms
o	Upstage AI's APIs integrate effortlessly with major platforms like Amazon SageMaker and Microsoft Teams, providing a flexible foundation for expanding your AI capabilities.
9.	Modular Components for Precision AI
o	Select only the modules you need—from OCR to text-to-SQL—allowing for highly targeted AI applications that minimize complexity and maximize functionality.
10.	Proven Scalability and Reliability
o	Our solutions are designed to scale effortlessly with your growing needs, providing reliable performance backed by the latest advancements in AI technology.
o	Upstage's on-premise solutions offer flexibility to scale AI capabilities as your business evolves.
11.	Multilingual Capabilities and Real-World Applications
o	Upstage AI excels in multilingual support, with high performance in languages like Korean, Japanese, and English.
o	Integration into platforms like KakaoTalk's 'AskUp' chatbot—servicing 1.65 million users—showcases practical usability and effectiveness in diverse linguistic environments.
12.	Top-Ranked Performance on Open LLM Leaderboards
o	Upstage AI's Solar 10.7B model holds the top position on the Hugging Face Open LLM Leaderboard, surpassing models from Meta and OpenAI.
o	With an average score of 74.2, Solar 10.7B outperforms GPT-3.5 Turbo (71.07) and Meta's LLaMA 2 (67.87), demonstrating superior capability in handling complex NLP tasks.
13.	Superior Mathematical Reasoning Performance
o	Upstage AI's Solar models, especially the 13B model, have achieved state-of-the-art performance in mathematical reasoning tasks.
o	This model surpasses competitors like ChatGPT and Microsoft's ToRA 13B on benchmarks such as GSM8K and MATH, with an accuracy improvement of over 10% compared to GPT-4.
14.	Top Performance on Open Leaderboards
o	The Solar 10.7B model has secured the top position on the Hugging Face Open LLM Leaderboard, outperforming renowned models from major tech giants.

15.	Depth-Up Scaling (DUS) Training from Upstage AI: Benefit and Feature Analysis
o	Achieve Superior AI Performance with Lower Costs
o	Benefit: Upstage AI's SOLAR-10.7B model, using the Depth-Up Scaling (DUS) technique, achieves a high Model H6 score of 74.20, outperforming models up to 30 billion parameters like Mixtral 8X7B, while reducing hardware costs by up to 50%.
o	Feature: Utilizes the DUS technique to maximize performance by integrating pre-trained weights from base models into upscaled layers, reducing the need for extensive hardware and computational resources.
o	Save on Infrastructure and Operational Expenses
o	Benefit: Operate Upstage's AI models on smaller hardware setups, cutting hardware and energy costs compared to larger models like Meta's LLaMA 2 and Falcon 180B
o	Feature: The Depth-Up Scaling method optimizes model size and resource efficiency, allowing for powerful AI capabilities on a more affordable infrastructure.
o	Adapt Quickly to Diverse Use Cases with High Performance
o	Benefit: Easily customize and deploy Upstage AI's SOLAR-10.7B model across various applications, reducing the time and cost needed for fine-tuning while maintaining top-tier performance
o	Feature: Advanced fine-tuning techniques like supervised fine-tuning (SFT) and direct preference optimization (DPO) ensure the model is adaptable and robust in multiple language tasks.
o	 Gain a Competitive Edge with Industry-Leading AI Models
1.	Benefit: Leverage models like SOLAR-10.7B that rank #1 on the Hugging Face Open LLM Leaderboard, outperforming major competitors like Meta and OpenAI, ensuring you receive cutting-edge AI capabilities
2.	Feature: Upstage AI's Depth-Up Scaling technique enhances the model's efficiency and performance, positioning it ahead of larger, more resource-intensive models.
o	Democratize AI Across Industries with Flexible Solutions
1.	Benefit: Make AI accessible for businesses of all sizes, offering secure on-premise installations and API-based implementations tailored to sectors like healthcare, finance, and e-commerce
2.	Feature: Provides flexible deployment options to meet diverse customer needs, whether through local deployment or cloud-based APIs.
Summary: Upstage AI's Depth-Up Scaling (DUS) approach delivers high performance and cost savings, enhances adaptability, and maintains a competitive advantage, making AI more accessible across all industry verticals.

 
Key Benefits & Features (Excluding Benefit Statements)
1.	Cost-Effective Fine-Tuning
o	Upstage AI offers fine-tuning of powerful AI models with minimal hardware, resource usage, and cost, making advanced AI capabilities accessible to businesses of all sizes.
o	By balancing high performance with low-cost infrastructure and flexible pricing, we ensure that more businesses can leverage AI's transformative power without prohibitive costs.
2.	Efficient Use of Resources
o	Single GPU Optimization: Solar LLM models operate efficiently on a single GPU, reducing the computational power and associated costs typically required for fine-tuning large language models.
o	Depth-Up Scaling (DUS) Technique: Enhances performance without large-scale infrastructure, optimizing available computational resources crucial for processing large datasets or iterative training.
3.	Flexibility in Model Customization
o	Modular Components and APIs: Enable users to fine-tune models specifically for their domain or use case, reducing time and computational expense because only necessary parts of the model are retrained.
o	Domain-Specific Pre-Training: Offers pre-trained models optimized for specific industries like healthcare, finance, and law, which can be fine-tuned further with minimal data and resources.
4.	Accessible Pricing Models
o	Flexible Pricing Tiers: Include options such as a free tier and a reasonably priced Pro tier, making it cost-effective for businesses to experiment with fine-tuning without substantial upfront costs.
o	Subscription and Usage-Based Options: Ensure customers pay only for what they use, making it easier to manage costs during fine-tuning and align expenditures with project budgets.
5.	On-Premise Deployment and Data Control
o	Reduced Data Transfer Costs: On-premise deployment eliminates the need for expensive data transfers to third-party cloud services, a significant cost factor when fine-tuning large models on sensitive data.
o	Improved Security and Compliance: Keeping data on-site avoids costs associated with regulatory compliance, reducing risks of data breaches or leaks.
6.	Streamlined Developer Tools
o	Comprehensive Developer Support: Offers detailed documentation, tutorials, and a developer-friendly playground, reducing the time and effort required for developers to fine-tune models.
o	Rapid Experimentation Capabilities: Enable rapid experimentation and iteration, allowing teams to refine models quickly and cost-effectively without extensive external resources.
7.	Optimized for Practical Use Cases
o	Trained to handle real-world challenges like unstructured data and industry-specific needs, reducing the need for extensive retraining during fine-tuning.
o	Pre-Built Solutions for Common Applications: Provide a range of pre-built solutions and use cases that can be easily fine-tuned, lowering the barrier to entry and costs associated with custom AI development.
8.	Efficient Use of Resources
o	Fine-Tuning with Minimal Hardware: Upstage AI's models can be fine-tuned using minimal computational resources, reducing the typical costs associated with training large models.
9.	Accessible AI for All Business Sizes
o	By offering a balance of high performance and low-cost infrastructure, Upstage AI makes advanced AI accessible to both large enterprises and smaller organizations.
10.	Flexible and Scalable Solutions
o	Upstage AI's on-premise solutions offer the flexibility to scale AI capabilities as your business needs evolve, ensuring long-term value and adaptability.
Industry Specific Ideation
1.	Healthcare: Enhanced Patient Outcomes with Predictive AI Solutions / Improving Patient Outcomes and Operational Efficiency
o	Benefit Statement: Hospitals using Upstage AI's healthcare-specific solutions, like GatorTronGPT and BioGPT, have reduced readmission rates by 18% by enabling early detection of health issues through advanced natural language processing and predictive diagnostics. These tools streamline clinical documentation and patient data analysis, significantly enhancing both patient outcomes and operational efficiency
o	Key Benefit: Upstage AI empowers healthcare providers with advanced patient data analysis, predictive diagnostics, and personalized treatment plans.
o	Solutions and Features:
o	Expert APIs for Healthcare: Offers tailored intelligence that aids in early detection of potential health issues by analyzing vast datasets rapidly.
o	Document AI and Key Information Extraction: Automates the extraction of critical patient data, enhancing workflow efficiency and reducing manual entry errors.
o	Impact: Hospitals using Upstage AI have seen an 18% reduction in hospital readmission rates and significant improvements in patient outcomes through faster, more accurate diagnosis and treatment personalization

2.	Finance: Superior Decision-Making with Domain-Specific AI / Enhancing Decision-Making and Compliance
o	Benefit Statement: Financial institutions using Upstage AI's BloombergGPT and KAI-GPT models have achieved more accurate risk assessments and better investment decisions, with lower-risk portfolios. These finance-specific language models improve decision-making by analyzing unstructured data, automating repetitive tasks, and providing real-time customer service while maintaining stringent data security standards
o	Key Benefit: Upstage AI enhances decision-making for financial institutions by delivering precise data analysis and risk assessment tools.
o	Solutions and Features:
o	Finance-Specific APIs: Provides specialized models for financial document classification, entity recognition, and data augmentation.
o	Text-to-SQL Functionality (Coming Soon): Converts natural language queries into SQL, allowing financial analysts to access and query databases without needing deep technical knowledge.
o	Impact: Financial institutions utilizing Upstage AI have experienced more accurate risk assessments, improved investment decisions, and lower-risk portfolios, contributing to greater financial stability

3.	Education: Transforming Learning with Personalized AI Models / Personalizing Learning and Supporting Administrative Tasks
o	Benefit Statement: Upstage AI's MathGPT has outperformed ChatGPT and GPT-4 in mathematical reasoning tasks, making it a top choice for enhancing STEM education. These education-specific solutions also support personalized learning and automate administrative tasks, allowing educators to focus on what matters most: student success
o	Key Benefit: Upstage AI revolutionizes the educational landscape by offering personalized learning tools and efficient administrative support.
o	Solutions and Features:
o	MathGPT and Edu Stage: Achieves state-of-the-art performance in mathematical reasoning, providing highly accurate, AI-driven content that supports curriculum planning and grading.
o	Administrative Automation: Uses AI to streamline administrative tasks, allowing educators to focus more on teaching and student engagement.
o	Impact: Educational institutions report enhanced learning experiences and improved student outcomes by leveraging AI-driven tools for personalized education and efficient management.

4.	Legal: Streamlined Legal Research and Analysis
o	Key Benefit: Upstage AI optimizes legal research processes, improving accuracy and reducing time spent on manual tasks.
o	Benefit Statement: Legal professionals using Upstage AI's Blue J model can complete research up to 50% faster by leveraging pre-built summaries, real-time analytics, and comprehensive analysis of statutes and case law. This efficiency allows for more accurate predictions of case outcomes and improves overall productivity in legal services
o	Solutions and Features:
o	Legal-Specific APIs (Blue J): Offers domain-specific AI models that automate legal research by analyzing thousands of documents and previous decisions, providing quick access to relevant statutes and case law.
o	Document AI: Automates the review of legal documents, contract summaries, and compliance checks, increasing productivity for legal professionals.
o	Impact: Legal firms using Upstage AI have reduced the time required for legal research by up to 30%, enabling lawyers to focus on more complex legal strategy and client interactions.

5.	E-commerce: Driving Sales and Customer Satisfaction with AI-Enhanced Engagement / Boosting Sales and Customer Engagement
o	Benefit Statement: E-commerce retailers implementing Upstage AI's tailored generative AI services, such as those developed with ConnectWave, have seen a 20% increase in sales conversions. These solutions drive hyper-personalization, enhance customer interactions, and streamline content marketing, resulting in a superior shopping experience and higher customer satisfaction
o	Key Benefit: Upstage AI enhances customer interaction and sales conversion rates in the e-commerce sector through personalized experiences and efficient operations.
o	Solutions and Features:
o	Generative AI Chatbots: Provides 24/7 customer support and real-time engagement, handling inquiries efficiently and improving the overall shopping experience.
o	Document OCR and Key Information Extraction: Streamlines the management of large inventories by automating the extraction of data from documents, reducing processing time.
o	Impact: An e-commerce giant reported a 20% increase in sales conversions and improved customer satisfaction after implementing Upstage AI-driven solutions, demonstrating a direct impact on the bottom line.

        """
    }, 
    {
        "name": "Customer Needs Analysis Ideation",
        "content": """
Part 1: Understanding the Importance of Discovery/Customer Needs Analysis
1.	Introduction to Customer Needs Analysis
o	We are only as successful as the quality of the questions that we ask: Our goal is assess, understand, consult, educate, equip and empower. See yourself as an educator, and as a physician of consulting. We must always assess our patient before recommending treatment.
o	Professionals provide consultative excellence, experience and solution design. Amateurs are transactional order takers.
o	Aligns Offerings with Customer Needs: Helps tailor solutions to actual customer challenges, increasing the likelihood of a successful sale.
o	Allows you to complete a 360-degree business assessment that 1) identifies Selling, Cross-Selling and Upselling Opportunities 2) Helps you assess customers implicit and explicit needs. 3) Equips you to shape and deliver a fully comprehensive presentation and solution set that provides and expanded ROI and value proposition for the customer. 4) Uncovers key technical, and non-technical requirements, environment information and other core aspects that assist in solution design and implementation.
o	Builds Trust and Relationships: 1) Demonstrates empathy and positions Upstage AI as a trusted advisor. 2) Establishes you as a consultative, subject matter expert.
o	Reduces Sales Cycle Time and allow for effective Sales Forecasting: By understanding needs upfront, it minimizes back-and-forth and speeds up decision-making.
2.	Interactive Exercise: Identifying Status Quo, Gaps and areas of opportunity for you (internally) and for customers.
o	Questions for Leadership:
	What do we currently know about our customers' biggest pain points?
	How do we gather customer information today, and what might we be missing?
	What is your current, documented sales process? Implementation Process? Customer Lifecycle Process?
	What information do you require from a customer to insure a fast, efficient and successful solution design, implementation, and further, customer success?
	Currently, what list of questions do you use with and for customers, from pre-sales through implementation, and later, ongoing customer success and expansion?
o	Real-World Examples of successful implementations:
	Case studies where a thorough customer needs analysis led to significant sales success or where the lack of it resulted in lost opportunities?
	Examples of failed implementations and or negative customer feedback. What happened, Why? How can this be mitigated in the future via improved process? Key learnings?
o	Group Activity:
	Break into small groups to identify potential gaps in current understanding of its customer base. Discuss how closing these gaps could enhance sales outcomes.

Part 2: Developing a Customer Obsessed Discovery Process
1.	Define the most efficient format: word, excel, web-based tool
2.	Define the document outline, keeping in mind that this process must be customer and employee obsessed, and should have a linear flow.
3.	Example Outline (see example document provided by Jason Randall):
a.	Pre-Call Planning & Preparation Guidelines
b.	Key Benefit Statements recommended
c.	Open ended, strategic questions to kick off the meeting
d.	Permission to ask questions with a clear 'why' and benefit to them.
e.	Discovery Topics with bullet pointed questions, broken out by section.
f.	Procurement questions
g.	Post Presentation Section for setting up the next call and clear, time bound, working backwards next steps.


Part 3: Define Functional Areas & Table Stakes Questions – Examples for Upstage AI:

Note: These are placeholder examples that will need refinement. Edit, add to or remove based upon your professional knowledge. Headers can and should be removed and or combined where appropriate.
Note: it's essential that you stack rank the headers by importance, and identify the 80/20 of what you need to know for each section. Based upon the appointment length, you will need to prioritize the right questions, then circle back in future meetings.

Opening Example
•	What are your top objectives for today's meeting?
•	If Upstage AI could partner with you to solve 2-3 current major issues or strategic initiatives, what would they be? What are you currently doing to address them? Biggest roadblocks so far?
•	To help us make the best recommendations, and provide you with customized resources, we need to better understand your current environment and organizational needs – is it OK if I ask you a few quick questions? This will allow me to provide you with a clear set of potential solutions, while ideally saving you time and money.

1. Business Challenges and Objectives
•	What key business challenges do you want to solve with GenAI?
•	What have you done so far to address that? Any current efforts or implementations? If so, how are they going? What's going well? What's not going well? Why?  Who else are currently consulting with? Opinion so far?
•	Do you have a defined GenAI strategy and roadmap? (if so, define – if not, ask what their challenges/concerns are in defining one).
•	What specific goals do you hope to achieve (e.g., cost reduction, increased efficiency, improved customer experience)?
•	Which processes or workflows are most time-consuming or prone to errors?
•	How do you currently measure success, and which KPIs are most important to you?
•	Are there specific pain points that you believe AI can address?
•	How do you prioritize these challenges and objectives?
 
2. Strategic Planning and Long-Term Vision
•	How do you envision AI fitting into your organization's long-term strategy?
•	What future AI capabilities or expansions are you interested in exploring?
•	Do you have a roadmap for deploying new GenAI applications, projects, and workloads?
•	How do you plan to scale AI initiatives across different departments or business units?
•	Are you interested in building internal AI competencies or relying on external partners?
•	What are your expectations regarding ongoing innovation and staying ahead in AI advancements?
•	How do you foresee AI impacting your industry in the next 3-5 years?
 
3. AI Readiness and Capability
•	Have you implemented AI or machine learning solutions before? If so, what were the outcomes?
•	How would you rate your organization's familiarity with AI technologies?
•	Do you have an internal team dedicated to data science, machine learning, or AI initiatives?
•	What level of expertise does your technical team have with AI frameworks (e.g., TensorFlow, PyTorch)?
•	Are you interested in custom model development, or would pre-built models suffice?
•	What are your expectations regarding model training, fine-tuning, and customization?
•	How do you handle data labeling and preprocessing for AI models?
 
4. Specific Use Cases and Industry Requirements
•	What industry-specific—or company-specific—challenges do you face that you think AI could help address?
•	Are there regulatory requirements or industry standards impacting your use of data and AI?
•	Can you share examples of how competitors or peers are successfully using AI?
•	Which tasks or processes do you believe could be automated or enhanced with AI?
•	Are there domain-specific datasets or ontologies critical for your AI applications?
•	How important is natural language processing, computer vision, or other specific AI domains to your use cases?
 
5. Strategic Planning and Long-Term AI Roadmap
•	What are your long-term plans for adopting new GenAI applications and workloads?
•	How do you prioritize AI projects within your organization's overall strategy?
•	Are there specific business units or departments targeted for AI transformation?
•	How do you plan to evolve your AI capabilities over the next 1-3 years?
•	What emerging AI technologies are you interested in exploring?
•	How do you foresee scaling AI solutions across global operations?
•	Are there plans for integrating AI with other emerging technologies (e.g., IoT, blockchain)?
 
6. Data and Infrastructure Assessment
•	Data Collection and Formats
o	What types of data are you currently collecting, and in which formats?
o	What types of data do you handle: structured, unstructured, or streaming?
o	How many data sources do you have?
•	Data Storage and Accessibility
o	How is your data stored, and how accessible is it for analysis and processing?
o	Do you have existing infrastructure that supports AI applications, such as cloud services, on-premises data centers, or hybrid environments?
o	Are you using any cloud compute resources?
o	Is hyper-converged infrastructure in place or under consideration?
•	Infrastructure Details
o	Number of on-premises servers (operating systems, general specs, age)?
o	Number of colocation servers (operating systems, general specs, age)?
o	What applications and infrastructure are you running?
o	What percentage of your workloads are virtualized?
	Do you use VMware or Hyper-V?
	Number of virtual machines (VMs) and across how many hosts?
•	Infrastructure Refresh and Purchases
o	How often do you refresh your on-premises environment? (Every 3 years, 5 years? When was your last refresh?)
o	Do you have immediate or pending purchases?
o	Which partner do you purchase through, and what are your plans for this year?
o	What is your annual contract spend and renewal month?
•	Data Management and Challenges
o	What challenges do you face in managing and utilizing your data effectively?
o	Are there any data quality issues or concerns we should be aware of?
o	How frequently is your data updated or refreshed, and how is it integrated across different systems?
o	What are your data volume and velocity requirements?
o	How do you handle data labeling and annotation for machine learning purposes?
•	Backup, Recovery, and Security
o	How do you currently back up or address disaster recovery for your systems and VMs?
o	How do you handle offsite backup and recovery?
o	What backup software do you use? (e.g., Commvault, Veeam, Veritas)
o	Have you considered cloud backup solutions (e.g., VMC on AWS)?
o	Are you concerned about scalability, availability, or security?
•	Data Growth and Storage
o	What is the total data storage currently managed (in terabytes), and where is it stored?
o	What do you expect for storage growth this year?
o	How long does it take you to add new storage?
•	Analytics and Visualization
o	Do you have plans or interest in analytics, AI, or machine learning?
o	What tools are you using for data visualization? (e.g., Tableau, Qlik, Power BI)
•	Administrative and Contact Information
o	Who are the administrative personnel or contacts involved in these processes?

 
7. Data Pipeline and Workflow
•	How do you handle data ingestion and preprocessing?
•	Are there real-time data processing requirements?
•	Do you require batch processing or stream processing capabilities?
 
8. Disaster Recovery and Business Continuity
•	What are your requirements for disaster recovery and business continuity for AI systems?
•	Do you have existing protocols the AI solution needs to integrate with?
•	How critical is data backup and recovery in your operations?
•	What is your acceptable Recovery Time Objective (RTO) and Recovery Point Objective (RPO)?
•	What is your current disaster recovery and/or business continuity plan?
 
9. Technical Architecture and Compatibility
•	Can you describe your current IT architecture, including hardware, software, and network infrastructure?
•	Which operating systems, databases, and middleware are you using?
•	Do you have a preferred cloud provider or platform (e.g., AWS, Azure, Google Cloud)?
•	Are there existing APIs or microservices architectures in place?
•	What programming languages and development frameworks are commonly used in your organization?
•	How do you manage version control and deployment pipelines (e.g., Git, CI/CD tools)?
•	Are there specific technical standards or protocols that our solution must adhere to?
•	How do you handle system monitoring and logging?
 
10. Security, Compliance, and Governance
•	What are your primary concerns regarding data security and privacy when implementing AI solutions?
•	Are there specific compliance requirements (e.g., GDPR, HIPAA, CCPA) that the AI solution must meet?
•	What security measures do you currently have in place (e.g., firewalls, encryption, access controls)?
•	How do you manage user authentication and authorization (e.g., IAM, SSO)?
•	Do you have data governance policies or practices we should be aware of?
•	What is your process for auditing and monitoring compliance?
•	Are there any third-party security assessments or certifications required?
 
11. Performance, Scalability, and Reliability
•	What performance requirements do you have for AI applications (e.g., latency, throughput)?
•	How do you anticipate your AI workload scaling over time?
•	Are there peak usage periods or specific times when demand increases?
•	What are your uptime and availability requirements (e.g., 99.9% SLA)?
•	How critical is fault tolerance and disaster recovery for your operations?
•	Do you require load balancing or auto-scaling capabilities?
•	How do you handle data redundancy and backup?
 
12. Integration and Deployment Preferences
•	Are you considering on-premises solutions, cloud-based deployments, or a hybrid model?
•	Which existing systems, applications, or platforms does the AI solution need to integrate with?
•	Are there specific APIs or third-party services that need to be considered?
•	How do you currently handle data integration and ETL processes?
•	Do you have a DevOps or MLOps pipeline in place for continuous integration and deployment?
•	What containerization or virtualization technologies do you use (e.g., Docker, Kubernetes)?
•	Are there any network considerations or limitations we should be aware of?
 
13. Budget and Investment Considerations
•	What is your budget range for AI projects, including initial and ongoing costs?
•	What kind of ROI or financial outcomes are you expecting from AI implementation?
•	Are you interested in flexible pricing models (e.g., subscription-based, usage-based)?
•	How do you prioritize budget allocation for AI and digital transformation initiatives?
•	Are there financial constraints or approval processes we should be aware of?
•	Do you have funding allocated for training and development related to AI adoption?
 
14. User Experience and Interface Requirements
•	Who will be the primary users of the AI solution (e.g., technical staff, end-users, customers)?
•	What are your requirements for user interfaces, dashboards, or reporting tools?
•	Do you have accessibility standards or guidelines we need to follow?
•	How important is customization of the UI/UX to match your branding or user workflows?
•	Do you require multi-language support for the user interface?
 
15. Support, Training, and Change Management
•	What level of support do you expect from your AI partner (e.g., 24/7 support, dedicated account manager)?
•	How do you prefer to receive ongoing support and updates (e.g., online portal, email, phone)?
•	What are your plans for training staff on new AI tools and technologies?
•	How do you handle change management and user adoption for new technologies?
•	Are there specific learning and development initiatives we can assist with?
•	Do you require documentation or training materials tailored to your organization?
 
16. Stakeholder Involvement and Decision-Making
•	Who are the key stakeholders involved in AI initiatives?
•	What are their roles and expectations regarding the AI project?
•	How does your decision-making process work for technology adoption?
•	What criteria are most important when selecting an AI partner (e.g., cost, expertise, scalability)?
•	How involved do you expect stakeholders to be during implementation?
 
17. Project Timeline and Urgency
•	Do you have a specific timeline or deadline for implementing AI solutions?
•	What factors are driving this timeline (e.g., market pressures, internal goals)?
•	Are there upcoming projects or initiatives the AI solution needs to align with?
•	How flexible is your timeline to accommodate integration and deployment challenges?
•	What are the critical milestones you aim to achieve during the project?
 
18. Performance Metrics and Success Criteria
•	What metrics will you use to measure the success of the AI solution?
•	How do you define success in terms of business impact, user adoption, or technical performance?
•	Are there benchmarks or targets we should aim for?
•	How frequently do you plan to review and assess the AI solution's performance?
•	Do you use specific tools or dashboards for performance monitoring?
 
19. Ethical Considerations and Responsible AI
•	How important are ethical considerations in your AI deployment?
•	Do you have policies regarding bias, fairness, and transparency in AI models?
•	Are there concerns about AI explainability or interpretability for your applications?
•	How do you plan to address potential ethical issues arising from AI use?
•	Are there diversity and inclusion standards you expect in AI solutions?
 
20. Legal and Contractual Considerations
•	Are there specific legal or contractual terms that need to be addressed?
•	Do you have preferred contractual agreements or Service Level Agreements (SLAs)?
•	Are there intellectual property concerns related to AI models or data?
•	How do you handle confidentiality and Non-Disclosure Agreements (NDAs)?
 
21. Communication Preferences and Cultural Considerations
•	What is your preferred method of communication for updates and discussions?
•	How frequently would you like to receive project progress updates?
•	Are there cultural or organizational norms we should be aware of?
•	Do you operate across multiple time zones or regions we should accommodate?
•	How do you handle language preferences within your organization?
 
22. Future Collaboration and Partnership
•	Are you looking for a long-term partnership for ongoing AI development?
•	How open are you to co-development or joint innovation initiatives?
•	What expectations do you have regarding collaboration on future projects?
•	How do you handle feedback and continuous improvement with your partners?
 
Additional Technical Questions
•	Model Requirements and Preferences:
o	Do you have preferences for specific AI models (e.g., transformer models, LSTM)?
o	What are your expectations regarding model accuracy, precision, and recall?
o	How important is model interpretability in your use cases?
•	Testing and Validation:
o	What are your requirements for testing and validating AI models?
o	Do you have datasets for validation and benchmarking?
o	How do you handle A/B testing or pilot deployments?
•	Deployment Environment:
o	Are there constraints on deploying containers or virtual machines?
o	Do you require edge computing capabilities?
o	How do you handle network latency and bandwidth considerations?
        """
    }
]

# Improve the generate button
if st.button("Generate Strategic Document", type="primary", use_container_width=True):
    for i, document in enumerate(documents):
        with st.status(f"📄 Processing: {document['name']}", expanded=True) as status:
            # Create two columns for the different models
            col1, col2 = st.columns(2)
            
            with col1:
                st.subheader("🚀 Solar Pro Analysis")
                try:
                    response = st.write_stream(get_response(document["content"], company_info))
                except Exception as e:
                    st.error("Solar Pro analysis failed. Please try again.")
                    st.exception(e)
            
            with col2:
                st.subheader("⚡ Groq Analysis")
                try:
                    response = st.write_stream(get_response_groq(document["content"], company_info))
                except Exception as e:
                    st.error("Groq analysis failed. Please try again.")
                    st.exception(e)
            
            # Add a progress indicator
            status.update(label=f"✅ Completed: {document['name']}", state="complete")

# Add footer with additional information
st.divider()
st.markdown("""
### About the Models
- **Solar Pro**: A powerful AI model optimized for business analysis and strategy generation
- **Groq**: A versatile language model capable of processing complex business documents

_Note: Results may vary based on the input provided. For best results, provide detailed company information._
""")