BUILD VS BUY

You can build the trust layer. Here's what that takes.

Your engineers can build it. The real question is whether you want them spending the next several quarters on trust-layer plumbing instead of the AI your business asked for.

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THE SCOPE

Seven domains before your first agent is production-ready.

0capability domains
0implementation phases
0maturity tiers

Anthropic’s Zero Trust for AI Agents framework defines what secure looks like. Building it yourself means delivering all of these:

Your build list: 0 items

  • Agent identity and authentication
  • Access control and privilege management
  • Resource boundaries and blast radius
  • Observability and traceability
  • Behavioral monitoring and response
  • Input and output controls
  • Policy, compliance and recovery

Then add the parts the framework doesn’t cover:

  • A trusted business-context layer
  • Data verification before AI reads it
  • Decision provenance your auditors will accept

THE COSTS THAT DON’T SHOW UP IN THE PLAN

Building is the easy part. Keeping it current is the job.

Specialist hiring

AI security, data governance and platform engineering, all at once.

A moving target

New models, new agent frameworks and new protocols like MCP arrive every quarter. Your controls have to keep up with each one.

New model

Evidence on demand

Regulators and auditors want answers in hours. Someone has to build and maintain the provenance pipeline.

Operations

Monitoring, incident response and upgrades, indefinitely.

Side by side

Build in-house: a multi-quarter platform program

TrustHouse: under a week

Time to production

Under a week from signed agreement

Where it runs

Your VPC, operated as a managed service

Keeping up with new models and frameworks

Included in the managed SLA

Trusted business context

Context Engine

Decision provenance

Built in

Lock-in

None. Your data, models and IP stay yours.

KEEP WHAT YOU’VE BUILT

TrustHouse wraps it. No rip and replace.

Point TrustHouse at any existing AI build on Bedrock, Vertex, Azure OpenAI or any model, and it comes under policy immediately. Your engineers keep building the AI. TrustHouse runs the trust layer around it.

BedrockVertexAzure OpenAIAny model

Questions

Yes. Policies, guardrails and corporate guidelines are yours to define. TrustHouse enforces them.

There's no software license to unwind and no architectural lock-in. Your agents, data and models stay where they are.

TrustHouse runs as a managed service inside your infrastructure, under an SLA.

Keep exploringWhy TrustHouseSecure AI GatewayReference Architecture

Your AI Is Making Decisions Right Now.
Can You Defend Them?

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