The architecture

Five layers. One governed system of context.

Data captured at the source, resolved and stored in a context engine only DashAPI builds, governed for trust, exposed through a model-agnostic interface, and turned into revenue action.

Capture

Data born structured, at the source

Omnichannel appKnowledge appField & Events appSalesforce · HubSpot · M365 · Google
The IP

Context Engine

The System of Context

Identity resolution & fingerprintingRevenue ontology · semantic modelEnterprise memory · knowledge graphVersioned data storeAutonomous enrichment agents

Governance

Why enterprises let agents act

Permissions & policy for agentsLineage & auditEU sovereignty · customer-held keys

Agent Interface

Model-agnostic

Retrieval: embeddings + graphTool callingOrchestrationAny LLM plugs in

Action

Where the budget moves

OutreachForecastsAlertsCross-team workflowsOutcomes captured back into the layer

One source of truth

Identity resolved across every channel, so agents work from one account and person graph.

Agent-ready by design

A semantic model agents can reason over, not free text they hallucinate around.

Enterprise governance

Permissions, lineage, audit, and sovereignty built for autonomous actors.

Where we are today

We're not pretending this is solved.

Identity resolution at enterprise scale, a revenue ontology that holds up across industries, a knowledge graph that stays current, governance an agent can be trusted against: each one is a genuinely hard problem on its own, and garbage-in stays a real risk for any system built on top of messy source data. We're in beta because we're still proving this out with real revenue teams, not because we've finished and are waiting to flip a switch. If you're evaluating us, ask us directly where we are on each of these. We'll tell you.

Ready to run your agents on trusted context?

Join the beta and be one of the first revenue teams on the System of Context.

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