AI made writing code trivial.
Getting it to production is still brutal.
We fixed the second part.
Your AI agent can ship a feature in 20 minutes. Then you spend three weeks gluing GitHub Actions, IAM policies, CloudFormation, secret managers, observability dashboards, and rollback runbooks before any of it sees a user.
StrictOps gives you a working pipeline on day one — three real environments (dev / stage / prod) provisioned in your own AWS account, owned by you, with the safety rails a real production system needs.
No CloudFormation. No Dockerfiles. No YAML hell. Just push code, ship code.
Your infrastructure,
your audit trail.
StrictOps never holds standing credentials, never proxies your traffic, and never stores your data. The control plane is the only thing we run — everything else lives in your AWS account, owned by you.
Cross-account IAM with external ID
StrictOps assumes a scoped role you create in your AWS account. We never hold standing credentials. Every action is recorded in your CloudTrail.
No shared infrastructure
Your services run in your AWS account on ECS Fargate. We never proxy customer traffic or host your data. Cancel us and your stack keeps running.
Promotion gates require approval
Production deploys require explicit human approval. Policies block secrets in logs and high-risk rollouts before they ship.
Audit trail in your CloudTrail
Every API call StrictOps makes lands in your own CloudTrail, with the assumed-role ARN and external ID attached.
Bring-your-own-keys for AI features
Log analysis is opt-in per organization. When enabled, log content is processed by Claude with redaction; we surface only summaries.
SOC 2 readiness on the roadmap
Enterprise tier ships with a SOC 2 readiness package, custom IAM boundary policies, and a dedicated onboarding engineer.
We slot in.
We don't swallow.
StrictOps is the layer between your AI tools and your AWS account. Your code stays in your repo. Your infrastructure stays in your account. Cancel us tomorrow and your production keeps running — because it's yours.
Two ways to ship the
thing your AI just wrote.
Pick whichever you prefer. We've heard convincing arguments for both.
Roll your own platform
- ✕ Wire GitHub Actions to AWS. Re-wire when IAM rotates.
- ✕ Write Terraform / CDK / CloudFormation by hand. Or learn one and migrate later.
- ✕ Build canary deploys, rollbacks, and error-budget gates from scratch.
- ✕ Stand up CloudWatch dashboards, log routing, alerting — yourself.
- ✕ Hire a platform engineer at $220K while runway burns.
- ✕ Discover you wrote a secret to logs three months in.
strictops init
- ✓ GitHub ↔ AWS link in one click. Rotation handled.
- ✓ Infra-as-code generated from your repo's reality, not your guesses.
- ✓ Canary, rollback, and error-rate gates wired by default.
- ✓ CloudWatch dashboards, log routing, alerting — bootstrapped.
- ✓ No platform engineer needed until you're past Series A.
- ✓ Policy guardrails block the dumb stuff before it ships.
See the architecture.
Read the docs for the exact IAM policy, CloudFormation templates, and audit event schemas. Or talk to us before you commit a single repo.
Ready to ship
with AI?
Vibe coding gets you to v1. StrictOps gets you to production — without learning DevOps.