The AI Control Plane
Govern agents, orchestrate providers, enforce contracts, isolate data.
AI Governance Engine
Runtime enforcement of agent behavior through capability manifests, approval chains, and action-level policy gates. Every AI operation is validated against tenant permissions, risk classifications, and operational boundaries before execution.
Multi-Layer Knowledge Architecture
Three-tier knowledge isolation: System, Partner, and Client. Each layer maintains independent vector stores with scoped retrieval boundaries. Automated document ingestion, domain-calibrated embeddings, and structured access policies ensure agents retrieve only authorized information.
Contract & Licensing Enforcement
Tiered licensing with per-partner usage metering, contract-bound entitlements, and automated billing. Feature access is enforced at runtime based on active license tier. Supports complex commercial models across partners, regions, and client hierarchies.
SDK-Based Secure Deployment
Embeddable AI delivered through iframe-isolated widgets with JWT-authenticated sessions and postMessage-driven communication. White-labeled under your brand, deployed inside your application, and governed by the platform.
Observability & Decision Tracing
End-to-end audit trails with correlation IDs linking every request to its agent, capability, action, and outcome. Decision logs capture the full reasoning chain. Usage ledgers track consumption for compliance and billing.
Provider Abstraction Layer
Model-agnostic orchestration across Gemini, GPT, Claude, DeepSeek, and custom models. Route requests based on cost, latency, capability, or policy. Switch providers without changing application code. No vendor lock-in.
Enterprise Scalability
Horizontal scaling with container orchestration, CI/CD automation, and production-grade monitoring. Deploy on managed cloud, hybrid, or fully air-gapped on-premise. Designed for sovereign data requirements.