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Structured Extraction is truly a Swiss army knife! Using Tensorlake's structured extraction API, you can summarize 200+ page PDF documents such as Claude 4's Model Card. What's cool is that you can specify the rules for summarization, suggest styles, request citations, etc.

Why aren't more people talking about how difficult it is to turn documents into structured data? This is literally a problem that every single company I talk to is trying to solve. They have a buttload of documents with forms and tables, and they want to turn them into usable

Santiago Companies sit on goldmines of PDFs, scans, and form, but can’t extract value without serious effort. Tools like Tensorlake are game-changers for operational intelligence.

Seeing a lot of demand for parsing Excel sheets in Tensorlake cloud from customers. What's a good representation that's helpful for building Knowledge Agents form excel sheets? The files we are looking at are WIDE and long. Think 100s of columns wide and 1000s of rows long.

Announcing Context-Aware Signature Detection in Tensorlake Cloud Signature Detection is a key aspect of business workflows, but ingestion APIs provide predictions related to presence/absence of signatures in documents and bounding boxes. Context-Aware signature detection in

We have been seeing a ton of usage of Tensorlake through n8n.io Time for us to build an official integration!

We are finishing up training of our new Document Layout Understanding model at Tensorlake. Getting great results on complex business documents such as the ACORD forms which are bread and butter for insuretech! 100% accurate detection of Forms and Tables in the same page. This

. Tensorlake now has the best Document Reading Order model among the open-source and vendor models that publish benchmarks. Surya OCR had the best reading order model to date. We are beating Surya's Reading Order model by 3% on the OmniDoc dataset. Reading Order detection is

Excited to be presenting with friends from Qdrant n8n.io about building Agentic applications with information that lives in Documents!

🤖LangGraph+ Tensorlake: Unlocking Document Understanding for Agents When creating agents that interact with data, the connections you have to that data matter Excited to announce an integration Tensorlake - a best in class document ingestion engine tensorlake.ai/blog/announcin…

📄🤖 Tensorlake Document Processing Tensorlake integrates with LangChain, enabling LangGraph agents to transform unstructured documents into structured data through their powerful multi-modal processing system. Learn more here 👉 tensorlake.ai/blog/announcin…

📄✍️ Real Estate Doc Agent Automate signature tracking in real estate documents by combining Tensorlake's signature detection + LangGraph's agent framework. Process, verify, and monitor signatures in one streamlined solution. Check out the tutorial 👉 docs.tensorlake.ai/examples/tutor…