Verifying Technical Truth.
Most VC due diligence stops at the pitch deck. We read the actual code. We dig into the infrastructure, test the benchmarks, and find the technical debt before you wire the money.
// Case Studies
The Cost of Unverified Tech.
HydraDB: The $6.5M "Vector DB Killer"
They raised $6.5M claiming their "ontology-first context graph" would kill vector databases. We looked under the hood. They were hardcoding prompts to beat benchmarks and passing off Anthropic's research as their own. Their in-memory setup meant hosting just 500GB of data would cost $10,000+ in RAM. At scale, they'd go bankrupt just running the servers.
Builder.ai: The Claims vs. Reality Gap
For years, Builder.ai claimed their AI was generating apps from scratch. It turned out they were mostly using offshore human labor. We run the audits that figure out if a startup's "proprietary AI" is real, or if it's just an API wrapper hiding a mechanical turk.
// The Team
Who's checking the code.
ML Engineer
Ayush Goyal
Undergrad at IIT Roorkee and former ML Engineer at Recepto.ai.
Blockchain Engineer
Yash Dugriyal
Undergrad at IIT Roorkee and Blockchain Engineer at Anthiaslabs.
Ready for a
Reality Check?
Stop funding vaporware. Let's look at their codebase before you sign the term sheet.
Get in Touch