ajainvivek

5 ms·

1. 1.▲
   by ajainvivek 1mo ago

   Ballet: the workflow is code; if the API exists we write against it, including internal ones. No drag-and-drop. If that isn’t a real difference for you, it will look like another Zapier, correctly. Check out the docs: https://doc
2. 2.▲
   by ajainvivek 6mo ago

   Benchmark We ran a small benchmark on a real-world insurance corpus: • 4 policy documents • ~1,900 hierarchical nodes • 100 queries across 6 complexity tiers Comparing ReasonDB to a typical RAG pipeline (LangChain / LlamaIndex defaults
3. 3.▲
   Show HN: Vector databases are the wrong primitive for AI agents(github.com)

   1 points by ajainvivek 6mo ago|1 comments
4. 4.▲
   by ajainvivek 7mo ago

   Your finding #2 is the most important — hallucinations are a retrieval problem, not a generation problem. We hit the same wall building legal document retrieval at Brainfish. Swapping embedding models gave incremental gains, but the real ju
5. 5.▲
   ReasonDB – A database that reasons through your documents(github.com)

   6 points by ajainvivek 7mo ago|1 comments
6. 6.▲
   by ajainvivek 7mo ago

   Hi HN, I built ReasonDB (Opensource) after spending 3 years building a knowledge intelligence layer at Brainfish (my company). We stitched together vector DBs, graph DBs, and custom RAG pipelines. The constant problem: when search returns t