The context engine for unstructured data
There are many steps in turning a mass of content into the perfect data slice for AI projects.
Deasy automates all of them.
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In seconds, generate domain-specific taxonomies and metadata
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90%+ classification accuracy across unstructured content
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Turn millions of files into an AI-ready knowledge base in under an hour
See how Deasy Labs works
in under a minute
Automate content discovery, tagging, filtering and enrichment
Deasy turns raw, unstructured content into high-quality knowledge bases that AI systems can reliably retrieve from—without building or maintaining custom pipelines.
Find the most relevant data, already tagged, deduplicated, enriched for AI, quality-controlled and with sensitive data filtered out. Slice it any way you want for your projects. Go.
Move your projects out of slow mode.
Prevent knowledge decay
AI systems fail when their knowledge goes stale.
Content changes. Taxonomies drift. Sensitive data reappears. What was once “AI-ready” quietly degrades.
Deasy continuously maintains your knowledge base—updating metadata and data products as your knowledge changes—so your AI stays accurate and reliable.
Deasy is the fastest way to create and maintain AI knowledge bases
It means less work, safer projects, better outcomes.
Get better AI results
Enriches data with a semantic layer, and removes irrelevant and outdated information to create more accurate AI retrieval.
Remove sensitive data
Classifies sensitive data so you can easily remove it from your data slice—your AI model never even sees it.
Skip the SME
Auto-learn a taxonomy from your data nearly as well as domain experts, and with the extra context AI needs.
Avoid rework
The knowledge bases can be automatically maintained and fed with new data over time to prevent model drift and support governance automation.
Save tokens
Use a mixture of AI & ML models in order to achieve more efficient token use, avoiding more brute-force methods with unoptimized LLMs.
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