Agentic AI on AWS · built for regulated workloads
Most agent demos put a model in front of your data and hope. This is the other thing: a deployed agent platform where every tool call is authorised before it runs, memory is encrypted per-tenant, and the whole stack is Terraform you can read in a pull request.
The mechanism
The interesting question about an agent is not what it can do. It is what it cannot do, and who decided. Follow a single tool call:
Governance
Not “do we have it?” but can the agent bypass it? Three honest answers, and knowing which is which is most of the job:
VPC-only networking with an egress allowlist, the managed runtime itself, Cedar at the gateway, organisation CloudTrail. The agent has no path around these because they are not in its control.
Model guardrails are real if every call goes through the gateway — and silently bypassed by a direct SDK call. Most teams believe these are hard controls. They are not.
Prompt management, orchestration style, evaluation discipline. A template can seed them; nothing enforces them. Pretending otherwise is how audits go badly.
PHI workflow
Regulated work fails on process far more often than on architecture. Three environments, identical infrastructure code, promotion by merge — and a human approval gate that exists in infrastructure rather than in a runbook.
AWS services can be HIPAA-eligible; architectures are not “HIPAA certified”. What this buys you is a Business Associate Agreement in force, PHI confined to services covered by it, encryption under keys you control and can revoke, US-region inference binding, and an audit trail that survives contact with an assessor. The controls are real. The certificate does not exist — and anyone selling you one is worth walking away from.
The decision space
None of this is one product with one shape. Each layer has real alternatives, and picking badly early is what makes agent projects stall in review. Highlighted is what a regulated healthcare deployment usually wants — not because it is the only answer, but because it is the one that survives an assessor.
The two that catch people out: memory defaults to a shared pool unless every caller is scoped, so one visitor’s context can surface in another’s answer — and encryption keys cannot be changed after the memory exists, so “we will add the customer key later” means rebuilding it.
Getting started
Nobody should begin with a platform. Begin with one workflow that is expensive, repetitive, and currently done by a person reading three systems at once.
Current-state review of your AWS or Azure footprint against the controls that agent workloads actually need: network egress, model access scoping, key management, logging retention, and where PHI would flow. You get a gap register and a prioritised roadmap. Fixed fee, no platform commitment.
Built on synthetic data, deployed through the same pipeline production will use. The point is not the demo — it is proving the promotion path, the approval gate, and the audit trail before any real data exists.
Cost caps, policy in enforce mode, per-tenant key isolation and alerting are provisioned before the first real request, not after the first surprise invoice. Then the second workflow costs a fraction of the first.
Evidence
Everything on this page describes a platform that is deployed and serving requests today. These are measured figures, not estimates.
destroy.
The part worth trusting is not that it works. It is knowing the ways it can appear to work while being wrong — a tool schema that silently drops every argument so the model invents them; a smoke test using curl without -f, which exits zero on an HTTP 500 and reports a broken deploy as green; a certificate renewed correctly while the gateway keeps serving the expired version it pinned months ago. Each of those was found and fixed here, and each is now a guard that fails loudly.
Next step
You have an agent proof-of-concept that security will not let near production. Or a compliance deadline and a platform nobody can explain in a pull request. Or you simply want to know what this would cost before committing to anything.
Fifteen years in healthcare IT, HIPAA and SOC 2 environments, AWS landing zones and Terraform — and the agent platform described on this page is one I built and operate, not a slide.
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