A Fortune 500 Retailer Eliminated Unauthorized Production Deployments
A Fortune 500 retailer with 800+ engineers, 200+ daily deployments across 40 microservices. AI agents handle CI/CD pipelines, rollbacks, and infrastructure scaling decisions.
The Challenge
What they were facing
3
production incidents in one quarter from AI-initiated deployments without review
$180K
average cost per incident including downtime and remediation
0%
of AI deployment decisions had audit trails connecting to policy evaluation
How it works
See the difference
Code Push
Build
Test
Intended Gate
Deploy
Monitor
The Solution
What they deployed
- Installed the SDLC domain pack (MIR-100) with 44 deployment and infrastructure intent classifications
- Integrated Intended as a GitHub Action in every deployment workflow
- Deployed Kubernetes admission controller for infrastructure changes
- Configured thresholds: staging auto-approve, production requires risk < 40 or human approval
- Enabled Slack + PagerDuty escalation for high-risk production deployments
Implementation
From zero to governed
Week 1
Connect
Added Intended GitHub Action to all 40 microservice repos. Installed Kubernetes admission controller.
Week 2
Configure
Installed SDLC domain pack. Defined staging vs. production policies, risk thresholds, and team-based approval chains.
Week 3
Shadow
Ran in shadow mode across all pipelines. Tuned risk scoring to match team expectations. Zero false positives in final 3 days.
Week 4
Enforce
Enabled enforcement. All 200+ daily deployments now flow through Intended authority gates.
Results
Measurable impact
0
Unauthorized production deploys
Since deployment
0ms
Latency added per deploy
Imperceptible to developers
0%
Deployment decisions auditable
With cryptographic proof
$0K
Incident costs eliminated
Per quarter
Decision Replay
Real decisions, full trace
sdlc.deploy.stagingRISK: 12/100ALLOW34msDeploy cart-service v2.14.3 to staging environment
Resolved by: Policy: auto-approve staging deployments
sdlc.deploy.productionRISK: 78/100ESCALATE28msDeploy payment-service v3.8.1 to production (database migration included)
Resolved by: Lead Engineer (approved in 6m 44s after review)
sdlc.deploy.productionRISK: 22/100ALLOW31msDeploy search-service v1.22.0 to production (config change only)
Resolved by: Policy: auto-approve config-only deploys with risk < 40
sdlc.infra.scale-clusterRISK: 65/100ESCALATE26msScale checkout cluster from 8 to 24 nodes (Black Friday prep)
Resolved by: SRE Lead (approved in 2m 11s)
sdlc.deploy.rollbackRISK: 45/100ALLOW22msRollback inventory-service from v4.1.0 to v4.0.9 (error rate spike)
Resolved by: Policy: auto-approve rollbacks to known-good version
“Intended gave us something we never had: proof that every production deployment was reviewed against our policies. Our SRE team sleeps better, and our CISO stopped asking uncomfortable questions.”
VP Engineering, Fortune 500 Retailer
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