DataQualifyUNSTRUCTURED

The unstructured companion to DataQualify

Turn every document into AI-ready data.

PDFs, contracts, emails, spreadsheets — 80% of enterprise knowledge is unstructured. DataQualify Unstructured parses, scores, governs and prepares it all, so your models and agents can finally trust it.

Explore modules
Runs fully local / air-gapped 30+ modules EN · TR · ES · DE
app.dataqualify.io/unstructured/home
DataQualify Unstructured — Home

Platform

Everything unstructured data needs to become AI-ready.

One platform covers the whole journey — from raw file to governed, agent-ready knowledge.

📄

Smart Parsing

PDF, DOCX, PPTX, XLSX, Markdown, scans — extracted with high fidelity, tables and structure intact.

🎯

AI-Readiness Scoring

Every document scored on parsability, completeness, consistency, freshness, clarity, structure and metadata.

🧩

Semantic Chunking

Chunk, embed and inspect the semantic structure of each document for reliable retrieval.

⚠️

Ambiguity Detection

Surfaces contradictions, stale content and conflicting statements before they poison your models.

🕸️

Document Lineage

Visualize versions, relationships and derivation across your entire corpus.

🛡️

Governance & Catalog

Ownership, classification and metadata coverage — a governed catalog for every file.

💬

RAG Playground

Query your corpus with retrieval-augmented generation and inspect answers and sources.

🤖

Autonomous Agents

Compose multi-step agent pipelines that parse, score and remediate documents on their own.

See it in action

Real screens, real documents.

Screenshots straight from the product — not mockups.

app.dataqualify.io/unstructured/readiness-dashboard
Readiness Dashboard

Executive scorecard of AI-readiness across your whole corpus.

Module suites

Nine suites, one platform.

Thirty-plus modules, organized into the way teams actually work.

How it works

From raw file to agent-ready knowledge.

01

Connect sources

Point Unstructured at your DMS, folders or mailboxes and sync every document.

02

Parse & analyze

Files are parsed, chunked and scored for AI-readiness automatically.

03

Govern & remediate

Catalog, classify and fix ambiguity, staleness and structure issues.

04

Feed agents & RAG

Serve clean, governed knowledge to your RAG apps and autonomous agents.

Integrations

Your sources, your LLMs.

Connect enterprise document sources and run any LLM — cloud or fully local.

🗄️Document sources
Local Folder
NFS / NAS Mount
SMB / CIFS Share
FTP / FTPS
SFTP (SSH)
CMIS ECM
AWS S3
MinIO
WebDAV / Nextcloud
Paperless-ngx
SharePoint
Google Drive
Confluence
Azure Blob Storage
Google Cloud Storage
IMAP Email
Box
Dropbox
Notion
🧠LLM providers
🦙Ollama
OpenAI
Gemini
OpenRouter
LM Studio
Local Qwen
Anthropic Claude
🤗HuggingFace

Don't see yours? Connect any S3-compatible store or OpenAI-compatible endpoint. Talk to us →

30+

modules

across nine suites

7

readiness dimensions

scored per document

100%

local option

air-gapped LLMs

4

languages

EN · TR · ES · DE

Who it's for

Built for the people who own the documents.

🏛️

Chief Data Officer

A single readiness score to prove the corpus is fit for AI.

⚙️

Data Engineer

Automated parsing and chunking pipelines instead of glue scripts.

🛡️

Governance Lead

Ownership, classification and audit across every document.

🤖

AI / ML Team

Clean, governed context so RAG and agents stop hallucinating.

📋

Compliance

Full audit trail and access control on sensitive content.

🔎

Analyst

Search and question the whole corpus in plain language.

Outcomes

Why teams adopt it.

AI projects ship faster

Stop cleaning documents by hand — readiness scoring and remediation are automated.

Agents you can trust

Only governed, unambiguous knowledge reaches your models and agents.

🔒

Nothing leaves your walls

Run every parser and LLM locally — sensitive documents never leave the building.

Security & deployment

Enterprise-grade, air-gap ready.

Deploy in the cloud, hybrid, or fully local — the choice is yours.

🔐

RBAC

Role and permission matrix with request-and-approve access.

🗝️

Encryption

Secrets and credentials encrypted at rest with Fernet.

🚫

Zero egress

Local LLM option keeps every document inside your network.

📜

Audit trail

Every action logged and traceable across the platform.

FAQ

Questions, answered.

Does my data ever leave my network?

No — you can run every parser and LLM fully locally (Ollama, LM Studio, local Qwen). Nothing has to leave your walls.

How is this different from DataQualify?

DataQualify handles structured, tabular data quality. DataQualify Unstructured is its companion for documents — the same platform family, different data shape.

Which document types are supported?

PDF, DOCX, PPTX, XLSX, Markdown, images and scans, including complex tables and mixed-type files.

Which LLMs can I use?

Ollama, OpenAI, Gemini, OpenRouter, LM Studio and local models like Qwen — swap providers per task.

Can agents act on documents automatically?

Yes — the AI Agent suite lets you build multi-step pipelines that parse, score and remediate on their own.

What languages does the UI support?

English, Turkish, Spanish and German, switchable at any time.

📅 Book a demo

Make your documents AI-ready.

A live demo with your own documents — see readiness scoring, governance and agents on your real corpus.

Runs on your infrastructure Local or cloud LLMs First corpus scan free