AI agents are brilliant.
The infrastructure feeding them is broken.

We close the Context Gap — giving AI agents the business understanding, economic efficiency, and governance to operate at enterprise scale. Without moving your data.

95% of GenAI pilots never reach production. Source: MIT, 2025.
$3.1 trillion annual enterprise AI cost crisis. Source: Enterprise Data.
$81,000 per month in hidden cloud infrastructure costs. Source: Average Enterprise.
60% of agentic projects will fail by 2028 without semantics. Source: Gartner D&A Summit, March 2026.

One data fabric, to power the context.

From cost recapture to ontology-grounded reasoning to governed agentic autonomy.

Phase 1: The Foundation

Virtualization Engine

Zero-copy data access + DuckDB edge caching. 80% of agentic queries served locally at zero marginal cost. No ETL. No egress. No data movement.

Up to 85% cost recapture

Phase 2: The Context

Ontology Engine

Formal ontologies (OWL/FIBO) map raw schemas to business concepts. Knowledge Graph + Context Graph for deterministic, auditable reasoning.

92.5% reasoning accuracy

Governance First

Built-in data governance with RBAC, RLS inheritance, audit trails, lineage tracking.

BCBS 239 ready & EU AI Act ready

Built on the open-source data stack

Three of the most powerful open-source data technologies. Two open standards. Zero vendor lock-in.

PostgreSQL

Ontology storage & Knowledge Graph

World's #1 database
DuckDB

Edge caching engine

6M+ downloads
Apache Iceberg

Open table format

Industry standard

MCP

Agent protocol

97M monthly SDK downloads
OSI

Semantic metadata exchange

Snowflake + Atlan + Salesforce

Built for regulated enterprise.

Financial services and healthcare. Where accuracy and governance are not optional.

AI agents are brilliant. The infrastructure feeding them is broken.