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Roadmap
Krishna Kishor Tirupati edited this page Jul 23, 2026
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PolicyAware is focused on practical, adoption-ready AI governance for LLM, RAG, MCP/tool, and AI-agent applications.
The full roadmap is maintained in the repository:
https://github.com/ktirupati/policyaware/blob/main/ROADMAP.md
- Deny-by-default policy enforcement.
- PII, PHI, secrets, and sensitive-data redaction.
- Local AI governance code scanning.
- MCP/tool governance.
- Risk-aware model routing.
- Runtime evaluation and audit traces.
- Optional ML and guardrails integrations.
- User feedback and testimonial collection.
- Add scan rules for more AI frameworks.
- Add more industry policy bundles.
- Improve HTML report usability.
- Add CI/CD examples.
- Add RAG and MCP examples.
- Add tests for policy and scanner edge cases.
- Private structured feedback form: https://docs.google.com/forms/d/e/1FAIpQLSc2QcQydjXZ0YF9bbVSpudoM5y8noxIP5jU-acVmjlyvf6Slg/viewform
- GitHub Discussions: https://github.com/ktirupati/policyaware/discussions
- Show and Tell: https://github.com/ktirupati/policyaware/discussions/categories/show-and-tell
- Home
- Capabilities
- Copy-Paste Examples
- Comparison
- SEO And Distribution
- Feedback And Testimonials
- Adoption And Impact
- Contributing
- Roadmap
- Ready-To-Use YAML
- Data Protection
- Policy Enforcement
- Gateway Orchestration
- Risk Classification
- Model Routing and Providers
- Tool Governance
- Evaluation
- Audit and Observability
- Guardrails Integrations
- ML-Assisted Signals
- Local Code Scan
- Installation
- Quick Start
- Architecture
- CLI Reference
- ML Integrations
- Provider Adapter Examples
- YAML Policy Templates