Prism finds it. Three intelligent layers that take raw data all the way to agent-ready context — without losing a single byte along the way.
Traditional databases were built for humans to query. Prism is built for agents to think with. Three layers, each with a distinct job, each feeding the next.
Raw data lands here first. Unfiltered. Unprocessed. Every byte, every record, every signal — regardless of whether it seems important right now. Because you can't know what matters until later. Nothing is ever deleted. Nothing is ever lost.
Prism's intelligent ingestion engine filters, classifies, and indexes what's relevant into structured, queryable form. The filter is always adjustable. And because the raw data is always safe in Layer 01, a wrong filter decision costs you nothing. Change it. Reprocess. Start over if you need to.
Structured data becomes semantic context. Compiled at ingestion — not at query time. Every chunk knows its own place in the larger picture before an agent ever asks for it. The agent receives exactly what it needs. Nothing more. Nothing less. No context window bloat. No noise.
Most AI data pipelines make you choose between completeness and usability. Prism doesn't. Every layer serves a different master — and all three talk to each other.
Your data source connects to Prism. Everything flows in. Congressional records, blockchain blocks, customer conversations, clinical notes, market data — whatever the domain, Capture holds all of it at full fidelity. The gene pool. Nothing is pre-filtered.
The Context Compiler runs. Each record is analyzed, classified, and indexed into structured form. Relationships are built. Patterns are flagged. Edge cases are surfaced. The filter decides what survives into structure — and because Capture is always intact, the filter can always be wrong without consequence.
Every structured chunk is augmented with situational awareness by a local model — before it's embedded. The chunk knows what document it came from, what role it plays in the larger picture, and why it matters. This intelligence is baked in at write time, not computed expensively at every query.
Your agent asks a question. Prism's hybrid retrieval — semantic and keyword simultaneously — finds the most relevant compiled chunks. A reranker filters to the top 2–3. The agent receives precision context, not a flood. Fewer tokens. Faster reasoning. Better answers.
Traditional databases were built for humans to query. Agents don't query. They reason. They need context, not records. Relevance, not rows. Precision delivered just in time — not a warehouse to wade through.
Prism is built for how agents actually work. The intelligence is in the data before the agent ever arrives. That's not a feature. That's a different architecture entirely.
Prism is domain-agnostic. The three-layer architecture works wherever there's raw data and an agent that needs to reason over it.
Prism is available by request. We'll scope your corpus, walk you through the three layers, and get your first pipeline running.
Request Access