Our Approach
Spec-Driven Development
Enforce conformance and custom requirements directly in the SDLC. Provide context only when it matters to keep AI workflows efficient and precise.
Continuous Improvement
Automatically measure, learn, and refine prompts, context, and guardrails to reduce token waste and keep integrations healthy.
Evidence & Observability
Instrument the SDLC with metrics, telemetry, and audit-ready evidence. Turn usage data into actionable reports that double as compliance artifacts and performance KPIs.
Technical Architecture
Dual-Layer Validation
Fast Deterministic Checks- Runs on every file save in milliseconds
- Catches known patterns: security vulnerabilities, code smells, style violations
- Context-aware analysis of your codebase and requirements
- Provides working fixes, not just warnings
- Catches subtle bugs and logic errors
- Enforces architecture decisions and custom requirements
Where Zenable Runs
IDE Protection Works with Cursor, Claude Code, VS Code, Windsurf, Codex, Amazon Q, Continue, GitHub Copilot CLI, Gemini CLI, Roo Code, Antigravity, and more. See our setup guide Pre-Commit Hooks Block bad code at commit time. Get started PR Reviews Automated line-by-line feedback with fix suggestions. We support both GitHub and GitLab.Custom Requirements
Upload your requirements once, enforce everywhere:- Architecture decisions
- Coding standards
- Compliance requirements (HIPAA, PCI-DSS, SOC2)
- Internal library usage rules
Key Benefits
- Catch bugs as code is written, not in review
- Speed up code review with automated first-pass
- Automatically meet company requirements
- Zero learning curve—works with existing AI assistants
- No CI/CD changes needed