TheHaze.ai turns enterprise knowledge into precise, model-ready context , so agents retrieve, reason, and answer from the right source. Context intelligence for enterprises.
Find signal across your multimodal corpus
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The bottleneck in most enterprise AI isn't the model — it's what never reaches it. 60% of organizational knowledge lives in unstructured formats: PDFs, slide decks, images, charts, clinical records.
TheHaze.ai is purpose-built to solve retrieval. Using tensor-backed search, multi-representation document embeddings, ML-powered learning-to-rank, and advanced query decomposition, we ensure your model receives the most relevant context — even for highly specific or domain-specific questions.
The result: retrieval accuracy that holds as you scale from prototype to production. Data stays in your VPC. You own the integration. We handle the hard part.
Surfaces precise, relevant context from PDFs, spreadsheets, images, audio, video, and legacy documents — simultaneously across your entire corpus.
Structures retrieved context for your LLMs in real time. No prompt engineering gymnastics. Just clean, grounded input that reduces hallucinations at source.
Eliminates redundant indexing passes and brute-force chunking. Only the signal your model needs — nothing more. Lower token costs, higher accuracy.
Runs in your VPC. Your documents never leave your perimeter. Audit logs, role-based access, and full data lineage included.
Handles unstructured text, tables, charts, scanned PDFs, images, presentations, audio transcripts, and internal wikis — all in one pipeline.
Ship TheHaze as a Docker container into any cloud. Exposes a native Model Context Protocol (MCP) server — plug directly into your UI
See how TheHaze exposes model-ready context through MCP so agents can retrieve from the right source without custom SDK work.
Copilot bundles retrieval inside a closed product. TheHaze is a retrieval engine you own — it runs in your VPC, connects via MCP, and optimizes for your corpus. You choose the model; we deliver the right context.
Lower token costs, full data sovereignty, and the freedom to swap LLMs without re-indexing. Only relevant context reaches the prompt — nothing more.
PDFs, slide decks, charts, scanned docs, and transcripts — indexed together. A question about a chart returns the chart and its narrative, not a random paragraph.
TheHaze uses LLMs, VLMs, and SLMs across embedding, query decomposition, and retrieval — and we benchmark open-source, cloud-native, and proprietary options so you get the best balance of cost and accuracy without doing the evaluation yourself.
Read on!
Do life sciences teams need a graph for semantic AI — or is hybrid retrieval enough? A tier-based decision framework for enterprise context layers.
Read article →
How to design retrieval that works in regulated life sciences — ingestion, hybrid indexing, ranking, and governed context packaging.
Read article →Tell us about your use case and we'll show you exactly how TheHaze can surface the context your models need. No fluff — just a focused 30-minute session.