Trying to build a ChatGPT-based alternative to Inven (a $10K market mapping tool)

Hi all,

I'm working on building a ChatGPT-powered alternative to Inven, a market mapping and company discovery tool used in private equity. It helps identify companies in a specific vertical by filtering based on industry, geography, and size (using Linkedin data), super useful for sourcing and thematic work.

I love the product, but my firm won't cover the ~$10K annual fee so I'm exploring ways to recreate the functionality using chatgpt and other open tools.

I've never built something like this before, so l'd love any tips, advice, or references, especially if you've worked on anything similar.

Thanks!

5 Comments
 

Building a ChatGPT-powered alternative to Inven is an ambitious and exciting project! Based on the most helpful WSO content, here are some actionable steps and considerations to guide you:

1. Understand the Core Features of Inven

  • Market Mapping: Identifying companies in a specific vertical.
  • Filtering: Based on industry, geography, and size.
  • Data Sources: Likely integrates with LinkedIn or similar databases for company discovery.

2. Leverage ChatGPT for Natural Language Processing

  • Use ChatGPT to interpret user queries in natural language and convert them into structured filters (e.g., "Find SaaS companies in California with 50-200 employees").
  • Integrate GPT-4's ability to process and summarize large datasets for thematic work.

3. Data Sources

  • LinkedIn API: Essential for company data. Note that LinkedIn's API has strict usage policies, so ensure compliance.
  • Open Data Sources: Explore Crunchbase (free tier), OpenCorporates, or other public databases for company information.
  • Web Scraping: If APIs are limited, consider scraping public data (ensure legality and ethical use).

4. Tech Stack

  • Frontend: Use a simple web framework like React or Vue.js for user interaction.
  • Backend: Python (Flask/Django) or Node.js to handle API calls and data processing.
  • Database: PostgreSQL or MongoDB for storing and querying company data.
  • AI Integration: OpenAI API for ChatGPT functionality.

5. Key Functionalities to Build

  • Search and Filter: Allow users to input criteria (industry, geography, size) and return relevant companies.
  • Data Enrichment: Use APIs or scraping to enrich company profiles with additional details (e.g., revenue, employee count).
  • Export Options: Enable users to export results to Excel or CSV for further analysis.

6. Challenges to Anticipate

  • Data Accuracy: Ensure the data is up-to-date and reliable.
  • Scalability: Handle large datasets efficiently.
  • Compliance: Adhere to data usage policies and privacy regulations.

7. Resources and Tools

  • WSO Resources: Check out the Financial Modeling Resources and Excel Resources for inspiration on structuring outputs.
  • OpenAI Plugins: Explore plugins that can enhance GPT's capabilities, such as integrating with external APIs.
  • Community Feedback: Post updates on WSO forums to gather feedback and iterate on your tool.

8. Cost Management

  • Use free or low-cost tiers of APIs and tools during the development phase.
  • Optimize API calls to reduce costs (e.g., batch processing queries).

9. Iterative Development

  • Start with a Minimum Viable Product (MVP) focusing on one or two key features.
  • Gather user feedback and expand functionality over time.

This project has the potential to disrupt the market mapping space, especially if you can offer a cost-effective alternative to Inven. Good luck, and keep the WSO community updated on your progress!

Sources: GPT-4 & Microsoft Co-Pilot, ChatGPT: The AI Analyst Who Ate Wall Street, Walking away from buyside after associate years, McKinsey Who?, https://www.wallstreetoasis.com/forum/investing/solving-a-crazy-problem-the-daily-peel-52223?customgpt=1

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