Govern every agent from first deploy to final retirement
Agents have lifecycles. They're drafted, tested, promoted to production, deprecated when superseded, and retired when no longer needed. Roval tracks every state, enforces every gate, and preserves every record, so no agent reaches production uncertified, no deprecated agent is forgotten, and no retired agent leaves a compliance gap.
Agents are born. They're rarely retired.
A developer builds a proof-of-concept agent. It works. It stays running. The developer moves to another team, or leaves the company entirely. The agent keeps calling APIs, consuming tokens, and accessing data, with nobody responsible for it.
Meanwhile, the model provider deprecates the version the agent depends on. A framework releases a breaking change. An API the agent calls gets sunset. Nobody tracks these dependencies across the agent estate, so nobody knows which agents are about to break until they break.
And when an agent finally does get turned off, there's no documentation of what happened. No succession plan. No archive of its compliance records. In regulated industries, this is an audit finding waiting to happen.
Especially as we're talking and moving into things like agentic AI, where things are potentially happening in an autonomous way, there may be even further guardrails so that we don't do the wrong thing.
If you have agentic agents doing things in healthcare, it's a very complex and messy situation... it's even harder than human identity to control and to understand.
Seven states. One governed lifecycle.
Every agent in Roval follows a defined state machine. Transitions are enforced by the platform, not by process, not by documentation, not by hope.
From draft to retired: every transition enforced
Every state transition is recorded in an immutable audit log with actor, timestamp, and before/after state. Invalid transitions are blocked. You can't skip from Draft to Production. You can't retire an agent without documenting what happened.
See the registryHard gates, not guidelines
Tier 3+ agents cannot advance to Production without an active, non-expired certification. This is enforced by the platform. When an agent is in Staging and its certification has expired, the Production gate blocks the transition with an explanatory error.
See complianceEvery state has a purpose
Draft for registration. In Development for active building. Testing for validation. Staging for pre-production certification checks. Production for live monitoring. Deprecated for managed wind-down. Retired for permanent record preservation.
See lifecycle in actionKnow when a dependency changes before agents break
Every agent has dependencies: a model provider, a framework, integration libraries, data sources. Each dependency has its own lifecycle. Roval tracks them across the entire agent inventory and surfaces risk before it materializes.
Dependency alerts, not just a graph
When a model provider announces a deprecation, Roval surfaces every affected agent, sorted by risk tier, with days until impact. When a framework releases a breaking change, you see the blast radius before anything breaks.
See the registryFive dependency types, continuously monitored
Model providers, frameworks, data sources, APIs, and other agents. When an upstream agent is deprecated or retired, downstream agents are flagged for review. When an API gets sunset, you see every agent affected.
See dependency graphRetire agents without creating compliance gaps
When an agent needs to be retired, Roval provides the governance framework for a controlled transition.
Four steps to a clean retirement
Inventory dependencies. Preserve records. Manage succession. Execute decommission. Every step is enforced and logged.
See complianceFor regulated industries: the EU AI Act requires post-market monitoring records. SOC 2 Type II auditors will ask what happened to agents in scope during the observation period. HIPAA requires documentation of system decommissioning when PHI was involved. Roval's retirement workflow satisfies all three.
EU AI Act Art. 72 · SOC 2 CC6.5 · HIPAA § 164.310(d)Frameworks that require lifecycle management
Lifecycle governance is a legal requirement under these frameworks.
Article 9 requires risk management as a continuous iterative process. Article 72 requires post-market monitoring throughout the system's lifetime.
Clause 8.4 requires documented lifecycle processes including planning, design, verification, deployment, operation, and retirement.
GOVERN 1.5 requires ongoing monitoring and periodic review of AI system risk, including processes for decommissioning.
CC6.5 requires disposal processes for system components. CC8.1 requires change management. Agents entering and leaving production are in scope.
Lifecycle management is built into every module
Every lifecycle state flows directly from the agent registry into compliance tracking and audit evidence. Lifecycle management is a core capability of the AI agent management platform.
Agent Registry
Register agents, assign owners, classify risk, and enforce lifecycle gates from a single registry that stays current automatically.
Explore the registryCompliance & Certification
Risk tiers drive which frameworks apply. Certifications auto-expire by tier. Drift detection catches configuration changes after certification.
Explore complianceStop discovering lifecycle gaps during audits
Join the private beta. Full lifecycle governance setup takes under a day.