Your LLMs are hungry for data, but documents are messy 😩. DocStrange is the answer! Our open-source solution turns any document into clean, LLM-ready data with one command. Give your models what they need. 🔗 github.com/NanoNets/docstran… 🔗 pypi.org/project/docstrange/

Nanonets OCR-3 is the only OCR model you'll need in your agentic stack. The model API exposes five endpoints - /parse - structured markdown /extract - structured outputs in your schema /split - classify or split outputs based on content /chunk - context-aware chunks optimized for RAG /vqa - grounded answers with bboxes over sources We've specifically fine-tuned the model on edge cases where OCR repeatedly fails - complex tables, forms, non-trivial layouts.

With bounding boxes, you get exact coordinates for every extracted element. Use them for - 1. RAG citations 2. Feeding specific document regions to agents 3. Agent observability With confidence scores, you can measure reliability of every extraction. Pass high-confidence outputs directly, route low-confidence outputs to human review or a larger model. Use them to push your net accuracy to near 100%.

#changelog Introducing AI Agent Guidelines. 👉 changelog.nanonets.com/intro…

Introducing Nanonets-OCR2: a lightweight 3B VLM that transforms documents into clean, structured Markdown and is capable of VQA. We have trained the model on close to 3 million documents. It is multi-lingual and can handle handwritten documents.

@nanonets just shipped Nanonets-OCR2: new 3B VLM for OCR! LaTeX equations, tables, handwriting, charts, multilingual - it does it all! You can try it against your data with one command via @huggingface Jobs - no local GPU needed! The HF Jobs command/output from the model 👇

We're excited to share Nanonets-OCR-s, a powerful and lightweight (3B) VLM model that converts documents into clean, structured Markdown. This model is trained to understand document structure and content context, like tables, equations, images, plots, watermarks, checkboxes, etc

Just launched: The smartest AI-powered Resume Builder — 100% free, no strings attached! Try it now: resume.nanonets.com #jobsearch #resume #AItools #resumetips #careerdevelopment #nanonets

#changelog Flexible Model Training Options. Our “Improve Model” feature has evolved to provide greater flexibility and precision in selecting training files. 👉 changelog.nanonets.com/flexi…

#changelog Identify New Templates in Instant Learning Models. You can now identify and flag new templates in Instant Learning Models through an approval rule. . 👉 changelog.nanonets.com/ident…

Nanonets grabs $29M for AI back office agents @nanonets #AI #BackOffice #AutonomousAgents #Agents #Funding #Startups @Accel #Nanonets techstartups.com/2024/03/12/…

AI-based workflow automation platform @nanonets has raised Series B funding of $29 Mn (INR 240 Cr) 👇 The latest round takes Nanonets’ total funding to $40 Mn to date. The startup plans to deploy the fresh proceeds for research and development, improving algorithms for handling unstructured data and launching new products. Besides, it aims to fuel growth by scaling up marketing and sales efforts to capitalise on the increasing demand for AI-based solutions. Founded in 2017 by Sarthak Jain and Prathamesh Juvatkar, Nanonets helps businesses leverage AI to make workflow automation easier. To read more in detail, click here: 4-2.co/3wOTp4x #startup #fundraising #investment #artificialintelligence

@nanonets raises $29M led by @Accel for AI-driven workflow automation. Offering no-code solutions to extract insights from documents, integrating with ERP systems for streamlined processes. Funds to fuel R&D and scale sales efforts. #Nanonets #AIStartup #Accel

Workflow automation platform @nanonets raises $29 million led by Accel The AI-based platform aims to use the funds for #research and development to improve its algorithms, as well as for scaling its #marketing and sales efforts. economictimes.indiatimes.com…

. @nanonets' AI platform is helping businesses turn unstructured data into actionable insights. We are thrilled to welcome @sarthak_jain, @PJuvatkar, and the entire Nanonets team to the #AccelFamily. techcrunch.com/2024/03/12/na…