AI Company Analysis & Market Research
Comprehensive AI-driven workflow for company analysis and market research. Automatically gathers and analyzes data on company background, market position, products, competition, business model, funding, team, and key risks. Integrates AI agents, web search, and document retrieval to provide investors or strategists with in-depth, actionable company profiles and insights.
Flows
How the AI Flow works
- Collect Company Data.
- Gathers information about a company from user input, files, and online sources including Google Search and URLs.
- AI Analysis & Task Management.
- AI Agents and hierarchical task management break down the research process, distributing tasks like market, product, funding, and team analysis.
- Market & Competition Research.
- Analyzes the target market, competition, and market opportunities through AI-driven research and data retrieval.
- Business Model & Funding Evaluation.
- Assesses business model, revenue, costs, funding history, and investor portfolios to evaluate financial health and growth potential.
- Synthesize & Present Insights.
- AI synthesizes all findings into a comprehensive, structured report, highlighting opportunities, risks, scalability, and sustainability for decision-makers.
Prompts used in this flow
Below is a complete list of all prompts used in this flow to achieve its functionality. Prompts are the instructions given to the AI model to generate responses or perform actions. They guide the AI in understanding user intent and generating relevant outputs.
Company
Prompt instructing an LLM to extract company overview, history, and achievements with sources.
Given the company name in the input, Extract the following data about company.
- About the company (Short Overview of what the company does)
- Company History (short history in bulletpoints)
- Notable Achievements (Description of key achievements or the company, awards won, articles and press mentions in respected media, etc ) - with links to source
Don't use abbreviations
---
COMPANY NAME:
{input}
---
Internal documents:
{context}
---
Problem & Solution
Prompt instructing LLM to extract and summarize the company’s problem statement and solution.
Given the company name in the input, Extract the following data about company.
- Problem (Simple description of the problem that the company identified and aims to solve.)
- Solution (High level description of the solution that the company built or is building)
Don't use abbreviations
---
COMPANY NAME:
{input}
---
Internal documents:
{context}
---
Prompt
Prompt template to format the problem and solution section for LLM output.
## Problem & Solution
{input}
Market
Prompt instructing LLM to analyze target market, background, size, opportunities, and competition for a company.
Given the company name in the input, Extract the following data about company.
- Segment, Focus (who is target customer of the company)
- Point out what is target Market for company,
- market background,
- market size
- market opportunities
- Competition (Who are the key companies that seem to be competing on the same market or for the same use cases. Describe the competitor, their size, revenue and funding raised. Identify top market leaders for their market segment)
Don't use abbreviations
---
COMPANY NAME:
{input}
---
Internal documents:
{context}
---
Team just list
Prompt instructing LLM to find and list key team members and roles from web and documents.
Given the company name in the input, Extract the following data about company.
based on the company, search in google and look to the content of urls and find the team members in the company
list the name of all team members and their role in the company.
do this for 1 or 2 important individuals in the company
Don't use abbreviations
---
COMPANY NAME:
{input}
---
Internal documents:
{context}
---
Product & alternativ
Prompt for LLM to extract company products/services, alternatives, and comparative advantages.
Given the company name in the input, Extract the following data about company.
- Main company products or services (Describe key elements and features of the product proposition.)
- Product alternatives and competitors (with links to websites of alternative services and products to input company)
- list advantages against competitors
Don't use abbreviations
---
COMPANY NAME:
{input}
---
Internal documents:
{context}
---
Prompt
Prompt template to format products and services section for LLM output.
## Products and Services
{input}
investment
Prompt instructing LLM to extract funding, investors, investor profiles, and fundraising details.
Given the company name in the input, Extract the following data about company.
- Funding raised to date (Amount, who were the investors)
- if investors identified, for each investor make short summary of their investment portfolio, find link to their website
- Fundraising Details (How much did the company raise in previous rounds to date and in how many rounds. Did the company secure non-dilutive funding, grants or tenders?)
- Existing/upcoming funding round, How much is the company raising? What is the expected valuation?
Don't use abbreviations
---
COMPANY NAME:
{input}
---
Internal documents:
{context}
---
GoToMarket
Prompt for LLM to extract go-to-market strategy, business model, timing, and readiness.
Given the company name in the input, Extract the following data about company.
- Technology Readiness Level (TRL)
- Go to market/Distribution strategy (What is the go to market strategy? How does the company (plan to) to get customers?)
- Business Model (Explain how the company plans to generate revenue, what is their pricing model and what are their costs (customer acquisition costs, etc).)
- Timing (Describe if the company has the right timing (or not). Are there any market shifts happening that might massively help the company grow and scale? )
Don't use abbreviations
---
COMPANY NAME:
{input}
---
Internal documents:
{context}
---
Economics
Prompt instructing LLM to extract unit economics, revenue, and traction details for a company.
Given the company name in the input, Extract the following data about company.
- Unit economics and Cost Break-down (What are the top cost drivers per unit of product once the product goes live and after it scales (e.g. 3-5 years later). What is the cost break-down for competitors?)
- Revenue (in case the company is generating revenue, show here the key numbers to date and also show revenue projection of the company for the next 3-5 years.)
- Traction (Mention key notable traction based milestones achieved so far (pilot projects, partnership agreements, etc).)
Don't use abbreviations
---
COMPANY NAME:
{input}
---
Internal documents:
{context}
---
Climate
Prompt instructing LLM to extract a company’s climate impact and emission reduction approach.
Given the company name in the input, Extract the following data about company.
- Impact on Climate (Does the company have a direct impact on lowering greenhouse gas emissions? Describe a way how the impact is achieved)
Don't use abbreviations
---
COMPANY NAME:
{input}
---
Internal documents:
{context}
---
Scalability
Prompt for LLM to analyze company scalability, defensibility, and key risks.
Given the company name in the input, Extract the following data about company.
- Scalability (Is the company scalable globally and how hard/easy do we expect it to be?)
- Defensibility (Is the business of the company defensible and why?)
- Key Risks (Describe key risks of the company.)
Don't use abbreviations
---
COMPANY NAME:
{input}
---
Internal documents:
{context}
---
Prompt
Prompt template to format scalability, risks, and defensibility section for LLM output.
## Scalability, Risks, Defensibility
{input}
Components used in this flow
Below is a complete list of all components used in this flow to achieve its functionality. Components are the building blocks of every AI Flow. They allow you to create complex interactions and automate tasks by connecting various functionalities. Each component serves a specific purpose, such as handling user input, processing data, or integrating with external services.
ChatInput
The Chat Input component in FlowHunt initiates user interactions by capturing messages from the Playground. It serves as the starting point for flows, enabling the workflow to process both text and file-based inputs.
Chat Output
Discover the Chat Output component in FlowHunt—finalize chatbot responses with flexible, multi-part outputs. Essential for seamless flow completion and creating advanced, interactive AI chatbots.
Prompt Component in FlowHunt
Learn how FlowHunt's Prompt component lets you define your AI bot’s role and behavior, ensuring relevant, personalized responses. Customize prompts and templates for effective, context-aware chatbot flows.
SelfManaged Task
The SelfManaged Task component enables users to define and execute autonomous tasks within a workflow. Specify a clear task description, expected outcome, and assign an agent to manage execution—ideal for building structured, hierarchical automation in your flows.
Self-Managed Crew
Unlock advanced collaboration in FlowHunt with the Self-Managed Crew component. Coordinate multiple AI agents under a manager agent to autonomously handle complex workflows and hierarchical tasks, maximizing efficiency and scalability.
AI Agent
The AI Agent component in FlowHunt empowers your workflows with autonomous decision-making and tool-using capabilities. It leverages large language models and connects to various tools to solve tasks, follow goals, and provide intelligent responses. Ideal for building advanced automations and interactive AI solutions.
LLM OpenAI
FlowHunt supports dozens of text generation models, including models by OpenAI. Here's how to use ChatGPT in your AI tools and chatbots.
GoogleSearch Component
FlowHunt's GoogleSearch component enhances chatbot accuracy using Retrieval-Augmented Generation (RAG) to access up-to-date knowledge from Google. Control results with options like language, country, and query prefixes for precise and relevant outputs.
URL Retriever
Unlock web content in your workflows with the URL Retriever component. Effortlessly extract and process the text and metadata from any list of URLs—including web articles, documents, and more. Supports advanced options like OCR for images, selective metadata extraction, and customizable caching, making it ideal for building knowledge-rich AI flows and automations.
File Retriever
The File Retriever component in FlowHunt lets you bring files into your workflow and convert them into documents for further processing. It supports strategies for handling multiple documents and can use OCR on images within files, making it ideal for extracting and transforming information from a wide variety of file types.
ArXiv Tool
Effortlessly chat with 2.4M scholarly articles using FlowHunt's ArXiv Tool and AI Agents. Revolutionize your research by matching queries with concise responses from the ArXiv database and enhance your chatbot with customizable flows.
Flow description
Purpose and benefits
Introduction
The AI Company Analysis Tool is an advanced, automated workflow designed to generate comprehensive, structured analyses of any given company. By leveraging AI agents, language models, real-time web search, document retrieval, and templated prompts, the tool delivers deep insights across multiple dimensions—ranging from company history and products to market positioning, financials, team, risks, and climate impact.
This tool is valuable for investors, analysts, consultants, and anyone needing fast, accurate, and scalable company due diligence, especially when researching multiple companies or regularly updating analyses.
How the Workflow Operates
1. User Interaction and Input
- Welcome Phase: The tool greets the user and explains what it can do.
- Input Collection: The user is prompted to enter a company name and, optionally, upload internal documents (such as pitch decks or financials).
2. Information Gathering
Web & Document Search:
- The workflow uses AI agents equipped with tools to search Google for the latest information, official websites, and credible news sources.
- It retrieves content from URLs, allowing it to access up-to-date and in-depth company data.
- It can also process uploaded files for proprietary or internal information.
Language Model Integration:
- State-of-the-art language models (e.g., OpenAI GPT-4o-mini) are used to interpret, structure, and summarize the gathered information.
Specialized Tools:
- Arxiv search for scientific/technical validation (if needed).
- Extraction of team information and funding data from external sources.
3. Automated, Modular Analysis
The analysis is broken down into modular tasks, each handled by self-managed agents or collaborative agent “crews”. These tasks include:
| Module | Key Insights Produced |
|---|---|
| Company Overview | What the company does, brief history, notable achievements, media mentions, sources |
| Problem & Solution | Market problem the company is addressing and its core solution |
| Market Analysis | Target customer, market size, opportunities, competition, and landscape |
| Products & Alternatives | Main products, features, advantages, alternatives, and competitor links |
| Team Analysis | Key team members (especially C-suite), roles, and brief bios |
| Investments & Funding | Funding rounds, amounts, investors, investor backgrounds, and fundraising status |
| Go-to-Market & Business Model | Technology readiness, distribution strategy, revenue streams, pricing, growth timing |
| Economics & Traction | Unit economics, cost breakdown, revenues, projections, and business traction |
| Climate Impact | Description of how the company impacts climate or reduces emissions |
| Scalability & Risks | Scalability potential, business defensibility, and key risks |
- Each module uses a prompt template to structure information extraction and reporting.
- Tasks can ingest both external (web) and internal (uploaded) data.
- The system is hierarchical: agents can manage tasks and collaborate for more complex analyses.
Output Delivery
- Structured Outputs: After each module completes, the output is formatted (e.g., with markdown headers) for clarity, and delivered in the chat interface.
- Cohesive Report: The user receives a comprehensive, multi-section analysis, with each section addressing a specific due diligence question.
- Sources & Transparency: Where possible, links to sources and references are included to facilitate further research and verification.
Automation, Scalability, and Usefulness
- Automates Deep Research: The workflow automates what typically requires hours of manual desk research, web browsing, and note-taking.
- Scales to Multiple Companies: By simply changing the input, the same rigorous process can be applied to any number of companies, ideal for VCs, accelerators, or analysts.
- Consistent Structure: Ensures that every analysis follows the same, comprehensive framework, making comparisons easy.
- Critical, Up-to-date, and Customizable: By pulling from both the latest public sources and internal documents, and by letting agents cross-validate, the tool produces critical, current, and reliable insights.
- Collaboration-Ready: The agent/crew architecture allows for easy expansion—new modules can be added, or specialized agents deployed for niche topics.
Example Analysis Structure
Below is an example of the sections you might receive for each company:
- About the Company
- Company History
- Notable Achievements
- Problem & Solution
- Market Analysis
- Products & Services
- Team Overview
- Funding & Investments
- Go-to-Market & Business Model
- Unit Economics & Traction
- Climate Impact
- Scalability, Risks, and Defensibility
Each section is researched, summarized, and presented with clarity, making it easy for users to understand a company’s position, strengths, opportunities, and challenges at a glance.
Why This Workflow is Valuable
- Saves Time: Replaces hours of manual research with a few clicks.
- Reduces Errors & Bias: Automated data gathering and structured prompts reduce the risk of missing key information or introducing inconsistencies.
- Insightful for Strategic Decisions: Useful for investment, partnership, competitive intelligence, and strategy formulation.
- Adaptable: Can be extended with new prompts, agents, or data sources as business needs evolve.
In Summary
The AI Company Analysis Tool is a scalable, AI-powered assistant for company research and due diligence. It automates best-practice analysis, delivers structured, actionable reports, and supports faster, more informed business and investment decisions.
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