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Prompt engineering, management, and LLM observability platform.
Developer framework and LlamaParse service for parsing documents and building AI agents and RAG workflows over them.
Real-time web search and content-extraction API that grounds AI agents with fresh, structured data for research and RAG.
No-code platform to run AI, web-scraping and search workflows across thousands of spreadsheet rows in parallel for SEO and outreach.
Unified API that gives AI agents web scraping, search, document extraction, and social/enrichment data through one billed endpoint.
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- ✦Prompt management
- ✦Prompt evaluations
- ✦LLM observability
- ✦Team collaboration
- ✦Version control for prompts
- ✦A/B testing of prompts
- ✦Prompt Registry
- ✦Historical backtests
- ✦Regression tests
- ✦Usage monitoring
- ✦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
- ✦Real-time web search API
- ✦Page content extraction and crawling
- ✦LLM-optimized structured/chunked output
- ✦Built-in PII and prompt-injection filtering
- ✦High-throughput, low-latency infrastructure
- ✦Drop-in integrations with major LLM providers
- ✦No-code AI workflow builder
- ✦Batch processing of thousands of rows
- ✦Web scraping and search enrichment
- ✦Multiple LLM model support
- ✦CSV/JSON/Sheets import
- ✦Export to CSV, JSON, HTML, Markdown
- ✦Free SEO utilities
- ✦Unified API for search, scrape, and extraction
- ✦Smart routing across multiple data providers
- ✦Document and PDF structured extraction
- ✦Social and media data (YouTube, TikTok, LinkedIn, reviews)
- ✦People and company enrichment
- ✦MCP and CLI surfaces for AI tools
- →Scaling customer support automation with LLMs
- →Empowering non-technical teams with prompt engineering
- →Building personalized AI interactions
- →Debugging LLM agents
- →Improving content creation processes
- →Managing and monitoring prompts with a team
- →Parse complex documents for AI apps
- →Build RAG and agent workflows
- →Automate invoice and claims processing
- →Search across technical documents
- →Grounding AI agents with live web data to reduce hallucination
- →Building research or retrieval-augmented generation (RAG) applications
- →Powering AI-driven search assistants
- →Enterprise-scale agents needing reliable web access
- →Generating SEO content and metadata at scale
- →Lead enrichment and outbound personalization
- →Bulk web scraping and data extraction
- →Batch summarization and research
- →Feeding AI agents reliable external web data
- →Replacing several scraping and search subscriptions
- →Extracting structured data from PDFs and documents
- →Enriching leads with company and email data