Enterprise AI operations
Deploy AI agents. Govern them at runtime. Prove compliance — three independent engines, one coherent platform, built for regulated and high-stakes production.
Deploy / Govern / Comply
Each engine runs as its own microservice, coordinated through an event bus — scale and ship independently without fragmenting policy or audit.
Lifecycle, marketplace, multi-model orchestration, studio, sandbox, and deployment pipelines — independent scale, full observability.
Identity, permissions, real-time monitoring, anomaly detection, kill switch, HITL gates, and communication policy — enforced at runtime.
Dynamic rules engine, regulatory mapping, evaluations, immutable audit trail, and report generation — driven by database, not hardcoded logic.
Boards and regulators expect the same rigor for agents as for core systems. The cost of “shipping fast without guardrails” is now measurable.
$492M
AI governance software market (2026 segment estimates)
88%
Enterprises actively adopting AI in production workflows
40%
Agentic initiatives at risk without governance guardrails
AgentCompliant vs Microsoft Agent 365 vs IBM watsonx.governance
High-level positioning for enterprise architecture reviews. Final fit depends on your cloud estate, data residency, and existing GRC tooling.
| Dimension | AgentCompliant | Microsoft Agent 365 | IBM watsonx.governance |
|---|---|---|---|
| Architecture | Three independent engines + event bus | Microsoft 365 / Copilot ecosystem | watsonx enterprise suite |
| Agent lifecycle & deployment | First-class deploy engine & pipelines | Varies by workload; M365-centric | Model ops & governance-centric |
| Runtime governance | Permissions, HITL, kill switch, comms policy | Policy via Microsoft stack & partners | Strong model AI governance & risk |
| Compliance & audit | Rules engine, evaluations, immutable audit trail | Purview / compliance add-ons (org-dependent) | Deep GRC & watsonx.governance alignment |
| Extensibility | Plugin registry (connectors, models, rules) | Graph, Azure, partner integrations | IBM Cloud & Red Hat integration |
| Deployment model | Dedicated microservices per engine | Cloud / tenant model per Microsoft offering | Enterprise private & hybrid options |
Built for sectors where mistakes are expensive
Trading support, KYC adjacency, and model risk — with retention and audit that satisfy exam-ready expectations.
Clinical operations and research copilots with controlled data paths, approvals, and regulatory traceability.
Matter-aware agents with obligation mapping, privilege-sensitive logging, and partner-grade reporting.
Jurisdiction-scoped rules, transparency, and evidence packs for oversight and inter-agency workflows.
Supply chain and plant-floor agents with anomaly detection, safety gates, and integration to ERP and MES.
Plans loaded from the platform API
Tier names, prices, and entitlements come from live plan definitions — not hardcoded marketing copy.
Plans are temporarily unavailable. Configure NEXT_PUBLIC_GATEWAY_URL and ensure GET /v1/billing/plans is reachable.
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