Nexus is GA. Enterprise knowledge, compiled once, query-ready for agents. On Sierra's τ-Knowledge: GPT-5.2 +12% accuracy, -80% cost. GPT-5.5 same accuracy, -77% cost.
Read the full announcement: pinecone.io/blog/pinecone-…
Use @typesafeai's Jev model with Pinecone to rerank results with natural language criteria!
Usually with rerankers, it's hard to cleanly specify what should and shouldn't be returned in results.
Jev resolves this by refactoring the problem into evaluating against distinct
A new release of our Agent Skills and Docs eval library, Cultivar is available!
Now, use @typesafeai's Jev model to evaluate how well your agents use docs and Skill against specified tasks in Modal sandboxes.
This works great, because Jev allows for binary yes/no decisions
Dozens of vector quantization papers come out every year. When we surveyed them, we noticed that most quantizers are not new algorithms. They are the same handful of primitive operations, strung together in a different order.
So we built VQ-bench: an open-source library of those
A database knows where your data is. A vector database understands what your data means.
It finds information based on similarity and meaning, not just exact keywords, powering semantic search, RAG, recommendations, and agent memory.
See how it works: pinecone.io/learn/vector-d…