Why TrustHouse
Your model vendor secures its workspace. Your catalog manages your data. Your security stack watches the network. The decision your AI makes sits between all three, and none of them own it. TrustHouse does.
The gap
Covers
Who can use the assistant, what gets retained, which connectors are on.
Stops
At the vendor's edge. Agents you build elsewhere and other models are out of scope.
Covers
Data quality, lineage, definitions and access before AI reads it.
Stops
Before the agent acts. The action itself happens somewhere else.
Covers
Content checks on each model call.
Stops
At the single call. No shared identity, context or decision record across your estate.
Covers
Inventories, risk assessments, policy documentation.
Stops
On paper. Policy is recorded, and enforcement lives in another system.
Covers
Prompt injection, data leakage, attack patterns.
Stops
They don't know your business context or why a decision was made.
AI workspaces
Data catalogs
The decision
Cloud guardrails
AI policy registries
AI security tools
5 tools. 5 partial answers.
And one question every regulator, auditor and board will eventually ask: why did your AI decide that?
The TrustHouse layer
Context Engine grounds every answer in your entities, definitions and systems of record, so AI reasons with the business meaning your teams already agreed on. Data Integrity catalogs, profiles and verifies every data asset before AI touches it. Together they reduce hallucinations at the source.
Why now
Compliance and security need controls they can sign off on. TrustHouse gives them those controls on day one.
Teams deploy agents in Bedrock, Vertex and ChatGPT integrations outside central oversight. TrustHouse discovers them and brings them under one policy layer.
Without provenance, answering takes weeks of data engineering. With TrustHouse, it is a replay.
Obligations are phasing in now. TrustHouse supports compliance by producing the evidence as AI runs. EU AI Act
How it deploys
Under a week to live.
From signed agreement to trusted AI in production.
Native connectors.
Your infrastructure stays in place. The trust layer wraps it.
Managed platform service inside your VPC. The ease of SaaS with the control of on-prem.
Swap any model or cloud, any time.
You pay for a managed SLA. Your data, models and IP stay yours.
Compare
“We have ChatGPT Business”
See how TrustHouse fits“We use Atlan”
See how TrustHouse fits“We're a Microsoft shop”
See how TrustHouse fits“AWS already gives us guardrails”
See how TrustHouse fits“We have an AI risk register”
See how TrustHouse fits“We bought an AI firewall”
See how TrustHouse fits“We'll build it ourselves”
See how TrustHouse fitsNot sure where you fit?
Claim Free EvaluationFAQ
TrustHouse doesn't replace your models, your cloud or your tools. It wraps them with one layer of context, security, risk and provenance, so what you've already built can go to production.
No. Point TrustHouse at what you've built on Bedrock, Vertex, Azure OpenAI or any model, and the controls apply immediately.
Nowhere new. TrustHouse runs inside your VPC, so data stays inside your perimeter.
Under a week from signed agreement to trusted AI in production.