Roadmap
Built around a simple product truth: AI systems moving into regulated workflows need signed evidence, deterministic governance, and operational controls that can survive audit.
What We Are Building
A cryptographic audit and governance layer for AI systems: signed Trust Receipts, independent verification, deterministic kernel decisions, and enterprise control plane workflows.
What We Are Not Building
- Not a foundation model company
- Not another AI chat interface
- Not a replacement for model providers
- Not just an observability dashboard
Phase 1: Verifiable Trust Receipts
Cryptographic evidence for governed AI interactions, designed to verify independently of the platform operator.
Phase 2: Canonical Governance Kernel
A two-tier governance model where semantic risk signals feed a deterministic kernel that remains the final authority.
Phase 3: Enterprise Hardening
Enterprise deployment controls around signing, content handling, auditability, and receipt lifecycle management.
Phase 4: Governance Orchestration
A constraint-aware governance control plane that coordinates sensing, analysis, action planning, and intervention workflows.
Phase 5: Federation & Advanced Controls
The next expansion is about broader deployment control, shared verification, and policy portability across organizations.
Experimental Research, Separated Clearly
We now separate production-critical controls from exploratory research work. That distinction is deliberate. Signed receipts, verification, runtime evidence, and the trust kernel are product-critical. Emergence-style heuristics remain experimental.
About This Roadmap
Delivered phases represent capabilities implemented in the current platform and supporting infrastructure. Planned phases are the next hardening and expansion steps, focused on customer-managed signing defaults, stronger policy portability, and cross-organization verification.