LlamaParse
LlamaParse is an enterprise document intelligence platform from LlamaIndex that converts unstructured files (PDFs, scans, images, Office docs) into clean, structured data for AI pipelines. It offers agentic OCR, schema-based extraction, classification, splitting, and RAG indexing via a single API, boasting 4x cost savings and 5x higher accuracy than frontier labs. Targeted at developers, data scientists, and enterprise teams building document agents or automating knowledge work in industries like finance, healthcare, and insurance.
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Added on
Sep 15, 2026
Monthly Visits
323.6K
Agentic OCR130+ FormatsStructured ExtractionRAG PipelineEnterprise SSOSOC2/HIPAAMulti-SDK
Product information
Everything worth knowing about LlamaParse
The complete picture — from everyday features to the technical detail builders and IT folks dig for.
Core features
What it actually does
Agentic Document Parsing
Turn complex layouts, handwritten notes, charts, and tables into clean, LLM-ready markdown using specialized AI agents for semantic understanding and auto-correction.
Structured Data Extraction
Extract specific fields (like names, emails, amounts) from documents into structured JSON or data schemas using LLM-powered agents, with no custom model training required.
Multi-Format Support
Parse over 130 file types, including PDFs, Office documents, spreadsheets, images, and scanned documents.
Document Classification & Splitting
Automatically categorize documents with natural-language rules and split combined files into logical sections for targeted processing.
Technical capabilities
Index & RAG Pipeline
Enterprise-grade chunking and embedding pipeline to build hosted vector search indexes for Retrieval-Augmented Generation.
Agentic OCR & Layout Detection
Proprietary technology that uses specialized agents to understand document layout, detect bounding boxes, and handle complex elements like charts and multi-page tables.
Must watch videos
2:00
Tutorial2:00
Introducing ExtractBench: The Most Comprehensive Benchmark for Data Extraction from Enterprise Docs
LlamaIndex is open sourcing the first schema-guided document extraction benchmark for the agentic era, ExtractBench. Document extraction is the foundation of every AI agent that operates on real-world enterprise files. But as agents gain autonomy and humans step out of the loop, existing benchmarks fall short of measuring extraction quality across the requirements production actually demands.
ExtractBench is an open-source benchmark testing 370 enterprise documents (4,869 pages) across 67 document schemas and 8 business domains. It jointly evaluates systems across the four dimensions production cares about most: long-record completeness, spatial visual grounding, perception robustness, and per-page cost.
LlamaExtract Agentic Plus was the only system to score above 90 on every dimension, leading the board at 95.6% overall.
Blogpost:https://www.llamaindex.ai/blog/introducing-extractbench
1:21
Review1:21
Deep Dive into Long-List Completeness: Evaluating Extraction Completeness on Long Documents
ExtractBench is an open benchmark for schema-guided document extraction. This deep dive looks at long-list completeness: how extraction systems handle multi-page, record-heavy enterprise files.
Every commercial VLM we tested scores well on short documents, then falls below 35% recall on documents past 50 pages, while precision stays high. The values that come back are correct. Most of the list doesn't come back at all.
ExtractBench scores long-list completeness with deterministic Hungarian alignment for record arrays and no LLM judge, so recall is measured exactly across complex schemas and multi-page filings, not estimated.
Read more about ExtractBench here: https://www.llamaindex.ai/blog/introducing-extractbench
1:06
Review1:06
Deep Dive into Perception: Scoring Scans, Handwriting, and Rotated Pages
ExtractBench is an open benchmark for schema-guided document extraction. This deep dive looks at perception: how extraction systems handle documents that don't arrive as clean, born-digital text.
ExtractBench tags every document by how the page was captured: born-digital, scanned, handwritten, or rotated. A system that reasons perfectly can still misread a smudged 5 as an 8.
The two frontier coding agents we tested have a perception blind spot, in opposite directions. One reads scans and handwriting well but stumbles on rotated pages. The other handles rotation and falls apart on scans and handwriting. LlamaExtract Agentic Plus is the only system that stays above 93% on all three.
Read more about ExtractBench here: https://www.llamaindex.ai/blog/introducing-extractbench
Who uses it
Real use cases, no hypeWhat's great
- Dominant performance on complex document benchmarks
- Massive format support (130+ types)
- Enterprise-grade security (SOC2, HIPAA, GDPR)
- Generous free tier for testing (10K credits/mo)
Technical strengths
- Agentic OCR with auto-correction loops
- Schema-based extraction without model training
- Multi-tier parsing (Cost Effective to Agentic Plus)
Where it falls short
- Credit-based system gets expensive at scale
- Not open source; commercial platform
- Advanced features locked behind Pro/Enterprise plans
- On-prem/VPC deployment requires Enterprise plan
Technical limitations
- Advanced tiers (Agentic Plus) significantly increase credit cost
- Concurrent job limits on lower tiers
- Index file caps (50-2K) may limit large-scale RAG
For technical folks
The deep-dive specs
API
REST API with SDKs for Python, TypeScript, Go, Java, and CLI
Architecture
Agentic AI pipeline with specialized experts for text, tables, charts, etc.
Deployment
SaaS (cloud), or VPC deployment for Enterprise
Compliance
SOC 2 Type II, GDPR, HIPAA
File Limit
130+ formats supported
Latency
Credit-based system; cost varies by parsing tier (Basic, Agentic, Agentic Plus)
Output Formats
Markdown, Plain Text, JSON, XLSX, HTML Tables, Annotated PDF
FAQ
Includes technical Q&ANo, LlamaParse is a commercial platform. The open-source project is LlamaIndex, which provides the foundational building blocks. LlamaParse offers a free tier.
Traffic Insights
Monthly Visits
323.6K
October 2026
Growth Rate
+26,5%
vs last month
Dominance
0%
in Search
Top Country
United States
26% of traffic
Top Countries Breakdown
United States
26%
India
6%
China
5%
Spain
5%
Canada
4%
Growth Trend
Rising
Consistent user growth over last 6 months.
Honest pricing
No sneaky tiers, no “contact sales”
Here's who each plan is actually for — and where the hidden charges might hit.
View Full Plans & Pricing on LlamaParse
Official pricing, checkout, and plan upgrades are handled directly on llamaindex.ai.
Reviews
What the internet actually thinks
Data refreshed weekly. No paid placements.
Trustpilot
Not reviewed yet
G2
Not reviewed yet
Capterra
Not reviewed yet
Product Hunt
Not reviewed yet
COMMUNITY COMMENTS
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Detail tags
Found via these searches
#OCR#DocumentParsing#VLM#LLM#Automation#DataExtraction#Enterprise