Your Agents Are Only as Smart as the Context They Have.
Context Engine gives every AI agent secure, governed access to the data and documents it needs to answer accurately, without giving the agent full access to your systems.
Three Ways Agents Get the Context They Need.
Database Intelligence
Agents Get the Data They Need. Nothing More.
When an agent needs information from a database, Context Engine retrieves only the relevant data and returns it to the agent, so the agent never holds full access to your systems.
Agents query through Context Engine, never directly.
A controlled retrieval layer that brokers every database request.
Only the relevant data leaves the database.
Minimum-necessary access by default. The agent gets the answer, not the dataset.
Every query is governed and logged.
Policy enforcement and audit trail built into every retrieval.
"What was account #4821's payment status as of last Tuesday?"
"What's our SLA on data-breach notification for EU customers?"
"TrustHouse will notify affected EU data subjects within 72 hours of confirmed breach discovery, in accordance with GDPR Article 33."
EU customers receive breach notification within 72 hours of confirmed discovery.
Document Intelligence
Answers, Pulled From Your Documents, Not Hallucinated.
Point Context Engine at your document repositories and your agents can answer questions grounded in your actual content, with citations back to the source.
Agents answer from your documents, not from probability.
Every response is grounded in retrieved content.
Source citations on every answer.
When an agent says something, you can see exactly where it came from.
Works across your full document estate.
Context Engine searches everywhere your documents live, not one upload at a time.
Data Synthesis Engine
Trusted Synthetic Data, Generated Under Governance.
Produce high-fidelity synthetic datasets for training, testing, and evaluation, without ever moving regulated data out of its safe perimeter.
Statistically faithful synthetic data, with no real records exposed.
Train, test, and evaluate on data that behaves like production, without the privacy risk.
The edge cases your production data rarely shows.
Generate long-tail scenarios for robust evaluation, training, and red-teaming.
Every synthetic record carries its own provenance.
Source schema, generation policy, and approved use cases travel with the data.
What This Means
Your agents answer from your data accurately, securely, and traceably.
Context Engine is how AI agents become genuinely useful in the enterprise without becoming a data risk.