AI Agent Governance for SaaS & Developer Tools
Your team adopted AI coding agents early — and now you're feeling the pain. PR volumes up 98%, review time up 91%, code churn rising. AI-SDLC gives you the governance framework to scale AI usage without sacrificing the quality your customers expect.
The productivity paradox is real
AI-forward teams are discovering that more AI output doesn't mean better outcomes — without governance, it means more rework.
AI tools increased PR volume by 98% — but without governance, more PRs means more review burden, not faster delivery.
Faros AI 2025
Review time increased 91% as AI-generated PRs flood the review queue with larger, harder-to-review changesets.
Faros AI 2025
Experienced developers using AI are 19% slower on mature codebases — despite believing they are 20% faster. A 39-point perception gap.
METR 2025
Code churn rose from 5.5% to 7.9% while refactoring dropped from 25% to 10% — more throwaway code, less structural improvement.
GitClear 2024
Scale AI usage without sacrificing quality
AI-SDLC gives engineering teams the governance framework to get the most out of AI coding agents — without the productivity paradox.
Complexity-Based Routing
Route AI-generated code through appropriate review gates based on task complexity. Simple changes flow through advisory mode; complex changes get full human review.
AI-Specific Quality Metrics
Track what AI actually delivers with purpose-built metrics — code churn rate, review cycle time, agent reliability rate, and DORA metrics layered with AI attribution.
Progressive Agent Autonomy
Agents earn trust through demonstrated quality. Start with full oversight, graduate to autonomous operation on proven task types. Automatic demotion on quality drops.
Multi-Agent Coordination
Govern multiple AI agents (Claude Code, Copilot, Cursor) through a single declarative framework. No more fragmented policies across tools.
Enterprise-ready compliance
Your enterprise customers are asking about AI governance. AI-SDLC gives you the compliance evidence they need to buy.
SOC 2
Immutable audit trails and quality gate enforcement provide the evidence SOC 2 auditors need for your AI-augmented development process.
ISO 42001
The first certifiable AI management standard. AI-SDLC's Plan-Do-Check-Act maps directly to ISO 42001 controls — differentiating your product in enterprise sales.
EU AI Act
If you sell to European customers, EU AI Act compliance demonstrates responsible AI practices — increasingly a procurement requirement.
Built for engineering-led organizations
From IC developers to the VP Engineering, AI-SDLC addresses the concerns of teams scaling AI coding agents.
VP Engineering
“AI tools increased output but quality metrics are declining and reviews are bottlenecked”
Measure actual AI productivity with purpose-built metrics. Complexity-based routing reduces review burden while maintaining quality standards.
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Staff Engineer
“Spending more time reviewing AI-generated code than writing code”
Progressive autonomy means proven agents handle routine work independently. Review effort focuses on high-complexity changes where human judgment matters most.
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Engineering Manager
“Can't measure whether AI tools are actually helping or creating hidden tech debt”
AI-specific metrics (churn rate, agent reliability, review cycle time) provide data-driven visibility into what AI is actually delivering.
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Ready to scale AI without the productivity paradox?
Start with the free Community edition or try Team Cloud for 14 days. Governance that helps your team ship faster — not slower.