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AI Infrastructure & MLOps Free

DocETL

Declarative LLM pipelines for extracting and transforming document collections

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PricingFree
Starting price$0 software
Free planYes
Free trialYes
APIYes
Open sourceYes
DeploymentSelf Hosted
Last verifiedAugust 1, 2026
Overview

Tool overview

DocETL is listed under AI Infrastructure & MLOps AI tools.

Summary

What is DocETL?

DocETL is an open-source system for building LLM-powered data processing pipelines over document collections. Users define declarative operations for extraction, classification, transformation, aggregation, and optimization without hand-building every prompt workflow.

Best fit

Best for

Data and AI teams building document, search, or analytics workflows

Audience

Who is it for?

Data engineersAI engineersAnalystsKnowledge platform teams
Recommendation

Decision note

Accepted for Preview after independent V411 official-source verification. Apply only after failures = 0, warnings = 0, unmapped = 0 and visible review of controlled values, Arabic v2, outreach, affiliate evidence, lifecycle, logo QA, and explicit clears.

Capabilities

Key features

Declarative map, reduce, and resolve operations

Pipeline optimization for quality and cost

Interactive workflow inspection and editing

Open-source execution over document collections

Workflows

Use cases

Extracting facts from document sets

Classifying large text collections

Resolving duplicate entities with LLMs

Building repeatable research pipelines

Strengths

Pros

  • Turns complex data into AI-ready workflows
  • Supports practical retrieval or extraction use cases
  • Official technical resources support implementation
Considerations

Limitations

Extraction and retrieval quality varies with document structure, data cleanliness, model selection, indexing strategy, and evaluation design. Teams should test representative content and verify important outputs before operational use.

Cost

Pricing details

Pricing modelFree
Starting price$0 software
Free planYes
Free trialYes
Pricing context

Billing options

Free open-source softwareExternal model costs
Pricing context

Pricing note

DocETL is free open-source software under the MIT License. Users pay separately for model-provider usage, compute, storage, databases, and any hosting or operational infrastructure.

View official pricing
Compatibility

Supported languages

  • English
Connectivity

Integrations

OpenAI-compatible models

Claude Code

Docker

YAML

Specs

Technical details

PlatformsWeb
Multilingual supportUnknown
Login requiredNo
Open sourceYes
LicenseMIT
DeploymentSelf Hosted
CompanyUC Berkeley EPIC Data Lab
Launch year2024
Current version0.3.0
Models / versionsExternal LLM providers
Editions / plansPython API YAML CLI DocWrangler UI
Data confidenceHigh
Last verifiedAugust 1, 2026
Documentation → Source code → Release notes → Data source →
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Answers

Frequently asked questions

DocETL is an open-source system for building LLM-powered data processing pipelines over document collections. Users define declarative operations for extraction, classification, transformation, aggregation, and optimization without hand-building every prompt workflow.
Data and AI teams building document, search, or analytics workflows
The listed pricing model for DocETL is free. Pricing can change, so users should verify the latest plan details on the official website.
Yes. The current profile indicates that a free trial is available.
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