I've been putting off creating a CRM tool, but I think it's about time. Maybe CRM is the wrong word: I need a tool to store info about all companies, investors, people, etc. to be able to build on down the road. The tipping point: I want to create a sustainable sourcing framework that scrapes data from X source weekly. (Again, I am too "lazy" to do this weekly myself -- I'd rather list all the sources I want to pull from, and have it run automatically.)
Part of this project is to see how long it takes to build something like this. I know a lot of folks are building these kinds of tools in Notion, but who wants to build a "Notion database" when you can build a more robust SQL one? I also think this sort of tooling is going to be critical scaffolding to build other AI tools on top of (e.g. document processing).
My full vision makes this a little clearer:
1. Create core data models. Create data models for "organizations" (companies and investors), funds, people, programs (e.g. a16z speedrun, DARPA) and cohorts, as well as all the relationships between them (company-to-person, investor-to-company, program-to-company, etc.). Allow users to create/update these. All built in Supabase (backend), frontend in Streamlit (for now).
2. Create data pipelines. Populate companies from websites. For example, a16z speedrun cohort 6 was recent; the pipeline should be able to pull from their website and pull companies and relationships.
3. Audit trail. See who updated the companies (pipeline? user?)
4. Add authentication, other usability tools. Let users log in via Google, email users when things are updated in the pipeline, make the scheduler work.
5. Add in investment details and company details. Right now we have the basics (basic company demographics, binary on whether an investment was made). Expand out to support a more full investment structure (e.g. X invested $Y in Z in Series A) as well as more robust company reporting ($X in revenue in 2025, etc.)
6. Add database partition? Find best way to make the database specific to a single investor, so that you can layer on multiple companies who can't see each others' data? (And try to stay in Streamlit for simplicity?)
6. Add in document processing. This is where it gets investor-specific. Process documents to extract revenue, investment #s, etc.
7. Add in other fun workflows? Allow users to connect their emails so you can see if you've emailed X company? Layer in automated meeting notes?
Hoping to be able to get through #1-3 this weekend; would be great proof-of-concept. The hard parts: database design (need well-designed database to withstand all future additions I'm planning!), knowing how to layer in the additions, knowing which order to tackle these in, knowing what the benefits/weaknesses of the tools (like Streamlit, SQL, scraping tools, etc.) are, hoping Google Antigravity is able to suss out what I want it to build with my instructions.
