AI Agent Governance for Platform Engineering
Your internal developer platform standardizes infrastructure, CI/CD, and security — but AI agents are the governance gap. AI-SDLC extends your IDP with declarative AI governance that works the way platform engineers think.
AI agents are your next platform challenge
You've standardized infrastructure and CI/CD. Now every team is adopting AI coding agents — and there's no standard for governance.
of enterprise implementations use multi-agent architectures — but no standard governs how agents interact across your developer platform.
Enterprise Surveys 2025
of shadow AI usage is growing faster than platform teams can track — fragmenting the golden paths you've built.
Salesforce 2025
drop in system stability per 25% increase in AI adoption — undermining the platform reliability SLOs you maintain.
Google DORA 2024
of agentic AI projects will be canceled by 2027 without governance — wasting the platform integrations you've built for them.
Gartner 2025
The governance layer for your developer platform
AI-SDLC extends your IDP with the Kubernetes-inspired declarative model platform engineers already think in.
Declare in YAML, Reconcile Continuously
Define AI governance policies in YAML — the same way you define infrastructure. The reconciler enforces desired state continuously, not just at merge time.
Adapter Architecture
Swap tools without changing governance policies. GitHub↔GitLab, Linear↔Jira, Slack↔Teams — adapters abstract the toolchain, just like Terraform providers.
Golden Path for AI Agents
Extend your golden paths to include AI agent governance. Define team-level policies, quality gate configurations, and autonomy levels in your platform templates.
Observability Built In
OpenTelemetry-compatible metrics for AI agent behavior. Export to Datadog, Grafana, or your existing observability stack. Track agent reliability alongside platform SLOs.
Cross-industry compliance coverage
Your platform supports teams across the organization. AI-SDLC provides the compliance mappings they need — regardless of their industry vertical.
EU AI Act
Risk-tier classification and transparency requirements map to AI-SDLC resource types — providing compliance evidence for teams building EU-facing products.
NIST AI RMF
Govern, Map, Measure, Manage — each function maps to AI-SDLC lifecycle phases. Provide NIST-aligned governance as a platform capability.
ISO 42001
Plan-Do-Check-Act maps to Pipeline spec, Agent execution, Quality gates, and Auto-remediation — enabling ISO 42001 compliance as a platform service.
Built by platform engineers, for platform engineers
AI-SDLC speaks the language of infrastructure-as-code, desired state, and reconciliation — because it was designed for how you work.
Platform Engineer
“No standard way to integrate AI agent governance into the internal developer platform”
Kubernetes-inspired declarative model fits your IDP natively. Define governance in YAML, enforce via reconciliation, observe through your existing stack.
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VP Platform Engineering
“Every team is adopting AI agents differently — fragmenting the standardized developer experience”
Provide AI governance as a platform capability. Teams get golden paths for AI agents; you get centralized policy enforcement and observability.
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Developer (Platform Consumer)
“Governance feels like friction bolted onto the development workflow”
AI-SDLC governance is invisible for low-risk work (advisory mode) and helpful for high-risk work (context-aware routing). Your AI tools keep working — they just get better.
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Ready to add AI governance to your platform?
Start with the open-source Community edition — it's Apache 2.0 and fits right into your Kubernetes-native stack. Upgrade to Team Cloud when you're ready for multi-team governance.