Agentic AI governance
Govern AI agents before they act.
AI agents do not just generate content. They call tools, touch data, trigger workflows, delegate tasks and operate at changing levels of autonomy. Gamut helps teams inventory agents, define boundaries, set human approval gates and capture evidence before agentic workflows become security, compliance or liability risks.
Book a callWhy agentic AI changes the assurance problem
Traditional model governance asks whether a model is appropriate, tested and monitored. Agentic AI adds a harder question: what is the system allowed to do? When an AI agent can access systems, retrieve records, create tickets, send messages, trigger code, update files or recommend decisions, governance has to cover action, authority, identity, oversight and evidence.
Agents are operational actors
They need owners, purpose, lifecycle status, autonomy levels, access boundaries, approval rules and review history.
Tool access creates risk
The risk is no longer just what an AI says. It is what it can touch, change, trigger, disclose or escalate.
Evidence must be captured as work happens
Boards, buyers, auditors and security teams need to see what was approved, blocked, escalated and remediated.
What Gamut helps you control
Agent register
Record each agent's purpose, owner, lifecycle state, autonomy level, tools, data access, suppliers, use case and risk context.
Human oversight
Map human-in-the-loop approvals, human-on-the-loop supervision and human-over-the-loop governance boundaries.
Tool and data boundaries
Define what an agent can access, what it can do unaided, what requires approval and what must be blocked.
Approval gates
Set decision points before high-impact actions, sensitive data access, external communications or operational changes.
Evidence packs
Capture assessments, controls, decisions, findings, remediation, approval history and residual risk in a reviewable form.
Board-ready reporting
Give leadership a concise view of agent exposure, control maturity, evidence quality, open gaps and decisions required.
The agentic operating layer: Agentic CISO, Gateway and Claw
Gamut is not just an assessment page for agents. It connects governance, approval decisions, controlled execution and evidence into one assurance operating model.
Agentic CISO
Records the agent, owner, purpose, autonomy, access, approvals, data flows, incidents, tests and assurance evidence.
Gamut Gateway
Acts as the decision point before AI-enabled actions move into business workflows, tools, systems or external services.
Gamut Claw
Runs approved AI tasks inside defined limits, with task scope, time limits, approved tools, result controls and governed evidence.
Controls your agent programme should be able to evidence
- Agent ownership and business accountability
- Agent identity, purpose and lifecycle status
- Autonomy level and permitted action types
- Tool allow-lists and permission boundaries
- Human approval gates for high-impact actions
- Human supervision and escalation paths
- Data access limits and redaction rules
- Runtime logging and decision records
- Incident, abuse and override playbooks
- Threat modelling and misuse testing
- Findings, remediation and residual risk
- Board, audit and buyer-facing evidence packs
Aligned to practical AI risk management
Gamut gives teams a practical way to align agent governance to the NIST AI RMF functions without turning the work into a static policy exercise.
Govern
Ownership, policy, risk appetite, approval rules, accountability and leadership reporting.
Map
Agent purpose, operating context, users, data exposure, tools, systems and supplier dependencies.
Measure
Autonomy, impact, control gaps, evidence quality, testing, findings and residual risk.
Manage
Remediation, monitoring, escalation, exceptions, approvals, audit review and continuous improvement.
30-Day AI Agent Assurance Sprint
For teams deploying GenAI, copilots or autonomous agents and needing a clear evidence base quickly. The sprint is founder-led and uses Gamut to turn agent governance into structured records, decisions and reviewable outputs.
What we produce
- AI system and agent inventory
- Autonomy and tool-access map
- Human-in, human-on and human-over-the-loop model
- Data exposure and system access review
- Control gap report and evidence quality review
- Board-ready AI assurance summary
Who it is for
- AI SaaS and agentic AI vendors
- Teams deploying Microsoft Copilot, Agentforce, ServiceNow AI, Workday AI or custom agents
- CISOs, risk, legal, compliance and internal audit teams
- Healthtech, fintech, insurance, HR technology and critical infrastructure suppliers
- Organisations preparing for buyer, board, insurer or audit scrutiny
Can you answer these questions?
- What agents are operating, being piloted or planned?
- Who owns each agent?
- What tools, systems and data can each agent access?
- What can the agent do without approval?
- Which actions require human approval?
- What evidence is captured when an action is allowed, blocked or escalated?
- What happens if the agent behaves unexpectedly?
- Can audit, legal, security or the board review the control history?
Founder-led AI assurance
Gamut was created by Arinze Okosieme, a cybersecurity and AI assurance practitioner with 27+ years' experience and CISSP, CCSP, CCZT and TAISE credentials. The platform is built for organisations that need practical control evidence, not another policy document.
Start with the agent assurance gap
Do not wait until agents are already acting inside the business.
Use Gamut to identify what exists, define what agents are allowed to do, put human oversight where it matters and produce evidence that leadership, buyers and reviewers can actually use.
Book a call