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Developer framework and LlamaParse service for parsing documents and building AI agents and RAG workflows over them.
Free all-in-one desktop AI app to chat with your documents and run RAG and AI agents fully local and private.
B2B sales research and data enrichment inside spreadsheets.
Data-foundation platform unifying product, customer, and order data via 2,600+ integrations to power AI agents for e-commerce ops.
Generative-AI infrastructure startup building production RAG pipelines, fine-tuning, and agentic systems for developers.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦LlamaParse document parsing and extraction
- ✦Open-source framework for AI agents and workflows
- ✦Document indexing for retrieval/RAG
- ✦Prebuilt solutions by industry and use case
- ✦Free starter credits for LlamaParse
- ✦Chat with your documents (RAG)
- ✦Runs locally and offline for privacy
- ✦Supports any LLM (local or cloud)
- ✦Built-in AI agents
- ✦Handles PDFs, Word, CSV, codebases
- ✦No-code setup
- ✦AI-powered text transformation, extraction, and summarization in Google Sheets and Excel
- ✦Automated web scraping and deep B2B research
- ✦CRM data enrichment and sales lead validation
- ✦Custom AI models and pre-built templates for data extraction
- ✦Scalable cloud infrastructure for large-volume data processing
- ✦Integration with CRMs (e.g., HubSpot) and REST API
- ✦Market-leading accuracy for data results
- ✦Unlimited data import and export
- ✦2,600+ native integrations
- ✦Two-way data synchronization
- ✦Unified single-source-of-truth database
- ✦Ready-to-deploy AI agents (PIM, pricing, enrichment)
- ✦Sits under automation tools (Make, Zapier, n8n)
- ✦Enterprise security (ISO 27001, SOC 2, GDPR)
- ✦End-to-end RAG pipeline engine
- ✦Rust-based document chunking
- ✦Model fine-tuning (low-rank adaptation)
- ✦Autonomous multi-agent systems
- ✦Model Context Protocol integration
- ✦Integrated coding/dev tools
- →Parse complex documents for AI apps
- →Build RAG and agent workflows
- →Automate invoice and claims processing
- →Search across technical documents
- →Privately querying your own documents
- →Running local AI without the cloud
- →Building AI agents over your data
- →Using multiple LLM providers in one app
- →Analyzing sales lists and generating keywords/SEO content
- →Automating B2B research and CRM data enrichment
- →Extracting company data, buying signals, and custom insights from websites
- →Building prospect databases and validating sales leads
- →Transforming messy text and unpacking survey responses
- →Drafting emails and outreach
- →Processing thousands of URLs simultaneously for research
- →Centralizing and cleaning product catalog data
- →Automating product enrichment and pricing
- →Syncing data across suppliers and channels
- →Powering AI agents on unified business data
- →Building RAG-based applications
- →Fine-tuning models to a domain
- →Multi-agent reasoning systems
- →Enterprise AI application infrastructure