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Data & context

Unstructured

Format-aware document partitioning that preserves structured elements and metadata before retrieval.

Overview

Research summary

Unstructured provides Python components for converting document formats such as PDFs, office files and HTML into structured elements and associated metadata. Developers use these outputs to prepare material for search, retrieval and language-model applications. Extraction strategies depend on the input format and may require OCR, layout models or additional system dependencies. This entry represents the Apache-2.0 open-source library. The company also operates a commercial platform and APIs with managed ingestion, enrichment and workflow capabilities; their feature set and service terms are separate from the library.

Repository summary

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Open issues
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Last push
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Commits, 90 days
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Repository activity
Not scored
Version
Unavailable

Recorded catalogue figures. View repository data and provenance →

Classification

Pricing & services

Paid services available

The provider offers paid products or services. Free options may also be available.

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Commercial offering checked 2026-10-02.

Licence scope

Implementation

Recorded implementation details and interfaces for Unstructured.

Implementation details

Python document partitioning library with format-specific extraction dependencies

Languages
Python
Repository type
source

Recorded interfaces and capabilities

Licence scope

Repository

Repository snapshots, release information and recorded maintenance signals.

Repository snapshot

Unstructured-IO/unstructured ↗

Stars
Unavailable
Open issues
Unavailable
Last push
Unavailable
Commits, 90 days
Unavailable
Repository activity
Not scored
Archived
Not recorded

Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).

Maintenance and provenance

Catalogue snapshot
2026-10-06

Documentation

Recorded references and research provenance for this entry.

Recorded sources 5

Research metadata

Research date
2026-10-01
Catalogue snapshot
2026-10-06

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