What does Unstructured do?

Unstructured provides a platform that converts messy, unstructured data into clean, structured data ready for generative AI applications. It supports over 64 file types and handles the full pipeline from extraction to loading. This helps teams prepare data for use with AI models.

What file types does Unstructured support?

Unstructured supports more than 64 file types, allowing it to handle a wide range of document and data formats. This breadth lets teams consolidate diverse sources into a single processing pipeline. The platform transforms these inputs into structured outputs for GenAI.

What does the ETL++ process include?

Unstructured's ETL++ process covers extraction, transformation, and loading, where transformation includes parsing, chunking, embedding, and enrichment. This goes beyond traditional ETL to prepare data specifically for generative AI. It produces data that is ready to feed into AI workflows.

Does Unstructured handle security and compliance?

Yes, Unstructured includes built-in security and compliance features as part of its platform. This is intended to let teams process sensitive data securely and continuously. Security is integrated into the data preparation pipeline rather than added separately.

Why is data preparation important for GenAI?

Generative AI models need clean, structured input to produce reliable results, but much real-world data is messy and unstructured. Unstructured automates this preparation so teams can focus on using their data rather than cleaning it. This reduces the time spent on data preparation complexities.

Startups AI Data Engineering Unstructured

Unstructured

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Transform complex, unstructured data into clean, structured data for GenAI applications, securely and continuously.

🏷 AI Data Engineering

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About Unstructured

What Unstructured does

Unstructured transforms complex, unstructured data such as documents, PDFs, and images into clean, structured data ready for generative AI and analytics applications. It provides the data pipeline layer that prepares enterprise content for AI, securely and on an ongoing basis, replacing fragile custom document-processing systems.

Key capabilities

The platform supports 64+ file types and handles parsing, chunking, embedding, and enrichment as part of an extended ETL workflow. It offers 30+ connectors to databases, data lakes, and enterprise systems, more than 1,250 pre-built pipelines, and both UI and API interfaces. Enterprise features include FedRAMP High, HIPAA, GDPR, and SOC 2 Type II compliance, role-based access controls, and 24/7 pipeline maintenance. It integrates with AI providers such as OpenAI and Anthropic and with partners including Databricks, MongoDB, and Pinecone.

Who it's for

Unstructured serves enterprise data engineering teams and organizations building AI workflows. Listed customers include McKinsey, JPMorgan Chase, Google, Amazon, Humana, and Bank of America.

Key capabilities

Transforms 64+ file types

Data extraction

Data parsing and chunking

Data embedding and enrichment

Seamless partner integrations (OpenAI, Anthropic)

Built-in security and compliance

Role-based access control

Optimized for any data destination

Technology stack

1detected May 30, 2026

Est. monthly stack spend ~$100/mo

Infra

Nginx

Agent readiness

15/100

Early

MCP server

Public API

Webhooks

OAuth 2.0

SDKs

No public agent surfaces detected yet.

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Frequently asked

What does Unstructured do?: Unstructured provides a platform that converts messy, unstructured data into clean, structured data ready for generative AI applications. It supports over 64 file types and handles the full pipeline from extraction to loading. This helps teams prepare data for use with AI models.
What file types does Unstructured support?: Unstructured supports more than 64 file types, allowing it to handle a wide range of document and data formats. This breadth lets teams consolidate diverse sources into a single processing pipeline. The platform transforms these inputs into structured outputs for GenAI.
What does the ETL++ process include?: Unstructured's ETL++ process covers extraction, transformation, and loading, where transformation includes parsing, chunking, embedding, and enrichment. This goes beyond traditional ETL to prepare data specifically for generative AI. It produces data that is ready to feed into AI workflows.
Does Unstructured handle security and compliance?: Yes, Unstructured includes built-in security and compliance features as part of its platform. This is intended to let teams process sensitive data securely and continuously. Security is integrated into the data preparation pipeline rather than added separately.
Why is data preparation important for GenAI?: Generative AI models need clean, structured input to produce reliable results, but much real-world data is messy and unstructured. Unstructured automates this preparation so teams can focus on using their data rather than cleaning it. This reduces the time spent on data preparation complexities.

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About Unstructured

What Unstructured does

Key capabilities

Who it's for

Key capabilities

Technology stack

Agent readiness

Alternatives

Databricks

Figure AI

Upscale AI

Dash0

Noma Security

Ineffable Intelligence

Frequently asked

Explore more around Unstructured

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