Data Ops AI apps

AI agents for document processing and enterprise data extraction.

Nanonets automates document-heavy workflows — invoices, orders, contracts, and claims — with AI agents that read, extract, and route structured data across ERPs, email, and approval chains. It runs on its own OCR-3 extraction model and can fold in LLMs for agentic pipelines. Offered as managed cloud with VPC, single-tenant, and on-premises deployment options and regional data residency.

Full-stack web scraping and browser automation platform for AI data.

A cloud platform for web scraping, data extraction, and browser automation built around 'Actors' — serverless programs that crawl sites and return structured data. Its store offers tens of thousands of ready-made Actors, and outputs clean Markdown or JSON that feed LLMs, vector databases, and RAG pipelines via LangChain and LlamaIndex. The company also maintains the open-source Crawlee crawling library for local development.

Agentic AI that automates document-heavy knowledge work and data extraction.

An operational AI platform from V7 Labs that builds and runs agents over complex documents — extracting financial, legal, and commercial terms, completing DDQs, and generating memos with source traceability. It chains foundation models from OpenAI, Anthropic, and Google into multi-step, auditable workflows aimed at finance, insurance, legal, and real-estate teams.

Open-source toolkit that turns documents into AI-ready Markdown and JSON.

A document-processing toolkit that converts PDF, DOCX, PPTX, XLSX, HTML, images, and audio into clean Markdown or JSON for LLM and RAG pipelines. It does advanced PDF understanding — page layout, reading order, table structure, and OCR for scans — and ships a hybrid chunker plus native LangChain and LlamaIndex integrations. Small enough to run on a laptop via a Python API or CLI; MIT-licensed and community-governed.

Open-source crawler that turns the web into clean, LLM-ready Markdown.

Crawl4AI is an open-source (Apache 2.0) web crawler and scraper built for AI pipelines, converting pages into clean Markdown or structured data for RAG, agents, and data pipelines. The core runs locally with no API key, handles JS rendering, and supports optional LLM-based extraction with any provider. It installs as a Python library/CLI or deploys as a Dockerized FastAPI server; a hosted Cloud API is in closed beta.

Agentic document parsing and extraction for AI teams, via one API.

A document-intelligence API that parses, splits, extracts, and edits PDFs, images, spreadsheets, and slides into clean, structured output for RAG and AI pipelines. It blends custom in-house models with frontier ones and bills via usage credits, automatically discounting pages it can parse without the heavier pipeline.

Open-source document intelligence API for RAG-ready data.

A document parsing and intelligence API that turns complex PDFs, slides, Word docs, and images into clean, LLM/RAG-ready chunks. Chunkr runs layout analysis, OCR, reading-order detection, semantic chunking, and schema-based extraction, emitting HTML, Markdown, or JSON. Self-host the open-source pipeline or call the managed cloud API, which includes a free tier of 200 pages with no card required.

Turn any webpage into structured data with one prompt-driven API call.

ScrapeGraphAI is an AI web-scraping tool that extracts structured data from pages and documents using natural-language prompts instead of CSS selectors or XPath, orchestrating LLMs in graph-style pipelines (single-page, multi-page, search, crawl). The core library is open-source under the MIT license with Python and Node SDKs; a hosted API adds a credit-based free tier and paid plans, plus integrations with LangChain, LlamaIndex, n8n, and an MCP server.

Open-source multi-type data labeling and AI evaluation.

Widely-used open-source tool for labeling and annotating data across images, text, audio, video, and time-series, with a standardized export format for training and fine-tuning. ML backends can pre-label data to speed up human review, and it increasingly doubles as a human-in-the-loop AI evaluation surface. Maintained by HumanSignal, which offers a hosted Starter tier and Label Studio Enterprise.

ETL for LLMs — turn PDFs, decks, and emails into clean, structured data.

Ingests 64+ file types and partitions, chunks, enriches, and embeds them into LLM-ready output, handling OCR, tables, and document hierarchy. An open-source library plus a low-code platform and API; a staple preprocessing layer for production RAG.

Turn any website into clean, LLM-ready data — scrape, crawl, search.

A web data API for AI — scrape, crawl, map, and search pages into clean markdown or structured JSON, handling proxies, anti-bot, and JS rendering for you. Open-source core (AGPL) plus a hosted service; a default web-ingestion layer for agents and RAG pipelines.