The tensorlake playground was, unlike AWS textract and every other tool I have tried, able to parse my angled, low-quality scan of Norwegian pay statistics from 1926. Not that 1926 Norwegian statistical tables is a generally useful benchmark…

Tensorlake@tensorlake.ai · 9mo ago

Document parsing benchmarks have been measuring the wrong thing. We tested every major parser on real enterprise documents. The results will change how you think about OCR accuracy 🧵

Document parsing benchmarks have been measuring the wrong thing. We tested every major parser on real enterprise documents. The results will change how you think about OCR accuracy 🧵

Want to build scalable data lakes w/ Tensorlake + @qdrant.bsky.social? In the free Qdrant Essentials Course, learn how to: - Architect vector-powered data lakes - Optimize ETL pipelines - Create knowledge graphs - Integrate @langchain.bsky.social agents for natural language queries t.co/OoPZswrL7z

New: Vision Language Models now power key document processing features We're using VLMs for: - Page classification in large documents - Table/figure summarization - Fast structured extraction (skip_ocr mode) Here's what this means for document processing 🧵

The company I work for, @tensorlake.ai, is hiring a couple of roles remote within the US: tensorlake.ai/careers You might be a great fit if you like working with Rust, Python, K8s, me?, and you enjoy building products for developers.

Tensorlake

Transform Data Into Knowledege

tensorlake.ai

Most parsers strip all tracked changes when you extract the text. That means: ❌ Lost audit trails ❌ Manual review of revision history ❌ No programmatic access to reviewer comments ❌ Workflows that can't route based on specific edits

OCR engines constantly mess up document hierarchy. Section 2.2 becomes a top-level header (##) instead of nested (###). We just shipped automatic header correction. 🧵 How it works:

Citations. When users ask "where did this come from?" your system should point to the exact page fragment...not just "file_name.pdf". Built citation-aware RAG with spatial metadata has: → Parse docs with bounding boxes → Embed citation anchors in chunks → Return page numbers + coordinates A 🧵

Job update: a couple of weeks ago, I joined @tensorlake.ai full time. I’m having a lot of fun building the product with @diptanu.bsky.social and the rest of this wonderful team. We have a few open positions if you’d like to work with us: www.linkedin.com/jobs/search/...

In finance, clinical trials, or performance benchmarks, dense tables contain mission-critical data. But flatten that data like most parsers do and trust is lost. Tensorlake restores trust by preserving structure, generating summaries for effective embeddings, and attaching evidence via b-boxes.

“Because the AI said so” isn’t good enough. Every answer should come with receipts (citations + context). Learn how to make your AI correct and verifiable in this month’s Document Digest newsletter 👇

The Document Digest by Tensorlake

Product updates and dev insights from the Tensorlake team.

tlake.link

You can now login into Tensorlake using Microsoft and Azure SSO credentials. This is the beginning of better integration with Microsoft Azure and Tensorlake. If you are using Azure, and need better Document Ingestion and ETL for unstructured data reach out to us!

To build trustworthy AI, your data needs proof. Get citations for every field extracted with Tensorlake. Read the blog and try our citations with the example notebooks: tlake.link/blog/citations

“RAG is dead” is lazy. What’s dead is cosine‑N without a retrieval plan. We ship advanced RAG...out of the box: • Classify pages → target sections • Extract structured fields → filter by form_type, fiscal_period • Verify data; cite page/bbox Want to know how? 🧵👇

Build a smart real estate agent (no license required). 🧠 LangGraph (by @langchain.bsky.social) + 📝 Tensorlake Contextual Signature Detection = ✅ Knows who signed ✅ When they signed ✅ If it’s ready to close Full tutorial + code linked below 👇

Most "unstructured" parses fail on when layout gets tricky: multiple columns, fragmented text blocks, mixed reading order Tensorlake doesn't. ✅ Authors parsed as one clean chunk ✅ Abstract follows, exactly as it should Unstructured ≠ unordered Preserve reading order. Parse with Tensorlake.

Over the last few weeks we have been working a ton on some huge improvements to the @tensorlake.ai API and SDK. They are finally live 🥳 More announcements around this is coming soon, but if you didn't see the announcement in our Slack, make sure you use v2 API and SDK 0.2.20 🙌

Want to see the tool in action? Check out this quick demo or try it out in the Colab Notebook (linked in the comments)

LangChain + Tensorlake: Unlocking Document Understanding for Agents

YouTube video by Tensorlake

youtube.com

Tensorlake@tensorlake.ai · last yr.

Just published 🐦‍⬛ langchain-tensorlake 💚 A new @langchain.bsky.social tool to parse real-world documents (PDFs, scans, forms) with Tensorlake & feed structured data right into your agents. Built for devs wrangling docs in legal, finance, healthcare & more. Learn more: tlake.link/langchain-tool

Just published 🐦‍⬛ langchain-tensorlake 💚 A new @langchain.bsky.social tool to parse real-world documents (PDFs, scans, forms) with Tensorlake & feed structured data right into your agents. Built for devs wrangling docs in legal, finance, healthcare & more. Learn more: tlake.link/langchain-tool

Tensorlake

Transform Data Into Knowledge

tensorlake.ai

Build a smart real estate agent (no license required). 🧠 LangGraph (by @langchain.bsky.social) + 📝 Tensorlake Contextual Signature Detection = ✅ Knows who signed ✅ When they signed ✅ If it’s ready to close Full tutorial + code linked below 👇

That one missing signature? It might delay a claim or void a contract Now in Tensorlake: Contextual Signature Detection → Detect handwritten, typed, or image-based → Trigger routing, alerts, or human review → API + SDK + Playground Read the full blog post tlake.link/signature-de...

Tensorlake

Transform Data Into Knowledege

tlake.link

21 hours later and we’re in the top 5 on Product Hunt! 🚀 Huge thanks to everyone who supported, upvoted, and shared 💚 Tensorlake is just getting started. Stay tuned - there’s so much more to come. P.S. There's still time to upvote our launch and let us know your thoughts 👇 #AI #RAG #LLM #devtools

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

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 pr...

producthunt.com

🚀 We’re in the top 3 on Product Hunt today just 6.5 hours after launch! Huge thanks to everyone supporting Tensorlake 🎉 From devs wrangling PDFs to teams automating high-stakes workflows. If you haven’t yet, check us out 👇

We just launched Tensorlake Cloud on Product Hunt 🎉 If you’ve dealt with messy document workflows and trying to parse complex documents (insurance claims, financial docs, multi-page forms), this is for you. Would love your support 💚 www.producthunt.com/products/te...

🔥 @diptanu.bsky.social has launched the cloud hosted version of Tensorlake. This looks pretty magical. The Pydantic support is so cool. Reminds me of @prefect.io's Marvin API. But Tensorlake purpose-built parsing for structured PDF (and other) documents.

Tensorlake@tensorlake.ai · last yr.

Announcing Tensorlake Cloud Up-leveling Document Ingestion and Workflows for building agentic applications and complex business workflows. www.youtube.com/shorts/OCv-...

Announcing Tensorlake Cloud Up-leveling Document Ingestion and Workflows for building agentic applications and complex business workflows. www.youtube.com/shorts/OCv-...