π Looking for investors tuned into your industry? π€ OpenAI's text embeddings got your back! Loaded GPT with 50k VC websites and Linkedin profiles. Categorised the investment focus. π Created embeddings for search based on the relatedness of text strings.
Thanks everybody for your upvotes. We are quickly going up! Let me share with you again our roadmap:
What has been done so far?
β Merged circulating investor lists from the internet
β Scraped each fund's web and Linkedin profile information.
β GPT Summarized what they say they invest in
β Deployed embeddings in a vector DB
β Connected with Google Sheets via our API
β π launched on Product Hunt π»
β Monthly sync with latest data from LinkedIn and web
β Scrape investor's website regularly for new investments
β AI analysis of portfolio companies to identify investor preferences
β AI analysis of portfolio companies to identify investor preferences
β Real-time investment team updates (who left, joined, got promoted)
β Search also within descriptions of (portfolio) startups
β Contacts on relevant founders (backed by your target investor)
β Outreach capabilities (pathway to your investor via relevant founders)
Looking forward to your feedback and feature requests!
ππ» Hey there, makers and entrepreneurs! We're thrilled to introduce our latest creation, which went viral on Linkedin last week (with 1M+ impressions and 4k comments)! π Thank you @adityavsc for Hunting us!
πAre you currently looking for investors tuned into your industry?
π€ OpenAI's text embeddings got your back!
We loaded GPT with 50k VC websites and Linkedin profiles. Categorised the investment focus. π Created embeddings for search based on the relatedness of text strings.
Sharing now π with all founders and VCs because fundraising is an uphill battle, research is the needle in a haystack, and 'spray and pray' is evil. π
π οΈ How to use it?
Enter your industry or what you do - instantly get a list of investors semantically related to your input based on their Linkedin, CB and website info.
What has been done so far?
β Merged circulating investor lists from the internet
β Scraped each fund's web and Linkedin profile information.
β GPT Summarized what they say they invest in
β Deployed embeddings in a vector DB
β Connected with Google Sheets via our API
β π launched on Product Hunt π»
β Monthly sync with latest data from LinkedIn and web
β Scrape investor's website regularly for new investments
β AI analysis of portfolio companies to identify investor preferences
β AI analysis of portfolio companies to identify investor preferences
β Real-time investment team updates (who left, joined, got promoted)
β Search also within descriptions of (portfolio) startups
β Contacts on relevant founders (backed by your target investor)
β Outreach capabilities (pathway to your investor via relevant founders)
π Ready to boost your fundraising effort with the AI-Powered VC Sheetβππ»ββοΈππΎ
βGet your free copy NOW (limited to 50 rows per query), or support the future development of this project by purchasing unlimited access to the full database, including regular updates and all future featuresβ
Great work guys! Finding the right investors consumes a lot of time and energy that we could invest into something more creative and worthwhile...
Congrats on the launch guys! Great tool for research! Definitely gonna check it out in more detail
Looks like a great product that would make every founders life easier who is seeking funding. Great work!
That's a brilliant idea, Just tested it out, and seems to be working perfectly, Going to purchase a license
@vlastimil_vodicka1 Any tool that helps Founders have better odds (chances) of getting funded is a worthy endeavour. I got frustrated with this problem 10 years ago and started consolidating data from various paid databases into macro-enabled MS Excel spreadsheets! Three points.
Most VCs don't invest until they see traction in the form of established and growing MRR. Do you intend to capture details of angel investors so that startups can access capital in smaller chunks at the pre-seed stage?
About 10% of VCs lead a round, i.e. issue a Term Sheet. The rest are follow-on investors. Will you be classifying VCs as lead investors or follow-on investors? If so, will that be based on what they say about themselves on their website, or based on what third-party websites such as Pitchbook, Crunchbase or Prequin say?
Most smaller VCs don't provide information about where they are in their capital raising and capital allocation cycle. VCs may take up to 12 months to raise the capital for a fund. They may then take up to 24 months or even longer to make initial and follow on investments. If a startup approaches them during their fundraising phase, they can't invest. If they approach them after they have made all their initial investments, they can't invest. The problem is, VCs tend to not want to say "no" right away. If you could include some guidance on the "in fundraising mode or fully raised" or "fully deployed or not fully deployed" modes, you would have a unique point of difference to every other platform in the market, other than the large, established, paid services like the ones I mentioned above.
This is such a cool concept. It's a time saver when researching who might be a relevant investor. If Vlastimil will continue improving the data, its accuracy, and its scope then this tool can be come a killer tool for any startup looking for investment.
@vlastimil_vodicka1 this is looking great. Congrats on the ability to ship fast from the Linkedin booming. I am looking forward to using this list asap!
Congrats on launching! Love that you are automating research... what are the future plans if this works out? Clearly many people enjoy the product