Tensorlake + Qdrant: Fast, filtered retrieval for structured and unstructured documents

Just dropped a new integration for developers working with real-world documents and vector search:

Tensorlake + Qdrant = structure-aware retrieval at scale.

Tensorlake API V2 and SDK 0.2.20

Over the last few weeks we have been working a ton on some huge improvements to our API and SDK.

They are finally live

📦 New Python Package: langchain-tensorlake

What s New

We just launched a native integration between LangChain and Tensorlake!

Now you can pass unstructured documents to a LangGraph agent and trust that parsing, chunking, and field-level accuracy are handled by Tensorlake s document engine no hacky pipelines required.

🚀 New Feature: Signature Detection just launched in Tensorlake!

Signatures might feel like a formality until they delay a claim, break compliance, or derail a deal.

That s why we built Signature Detection into Tensorlake, giving you the power to track and act on signature presence inside your documents:

Basic Detection

Samar Ali

2mo ago

Tensorlake - Parse documents like a human & build Python-based workflows

Tensorlake Cloud is a platform for document ingestion and data orchestration. Parse real-world documents with human-like layout understanding and build Python-based workflows at scale and ready for production.