Governed agent platform for regulated industries
Deploy agents. Prove every action.
Governed agents for healthcare, insurance and financial services, with just-in-time authority, runtime enforcement and evidence built into every run.
The agent works.
You still can’t trust it to act.
You can’t define its limits
Access lets the agent reach a system, but does not establish which data and actions are actually permitted.
You can’t stop the wrong action
When policies sit outside execution, teams discover violations after the agent has already acted.
You can’t prove what happened
When risk or audit asks what the agent did and why, no one has a complete answer.
Know the agent. Control the action.
Prove the outcome.
Difinity makes trust operational: every agent has an identity, every action starts with permission, policy stays in the execution path and every run leaves evidence.
Every agent has a job and an owner
Give each agent a defined purpose, identity and accountable owner before it touches a business system.
Every action starts with permission
Pre-approve the systems, data and actions it may use instead of handing it open-ended access.
Policy stays in the execution path
Apply policy and sensitive-data controls while the agent works, blocking or routing anything outside its authority.
Every run leaves evidence
Keep a clear record of what the agent attempted and completed, ready when risk or audit asks.
Start with one job.
Expand authority from evidence.
Define
Give the agent a job, identity and the instructions it needs.
Isolate
Run each execution in its own environment with limited access to compute, files and networks.
Connect
Expose only the approved systems and tools the job actually needs.
Govern
Apply action permissions, policies and PII protection while the agent works.
Record
Keep a clear record of every attempt, block, fallback and outcome.
One governed run.
Four teams can make a decision.
The same run record gives technology, security, audit and business owners the evidence each needs.
01Technology and AI
Did the agent complete the job reliably across the systems involved?
Actions, errors, fallbacks and outcomes are visible in the run record.
Improve the agent or expand its responsibility
02Security and risk
Did it stay inside approved access, data and action boundaries?
Identity, permissions, policy results and protected data are recorded together.
Keep, narrow or change its authority
03Compliance and audit
Can we produce compliance-ready evidence for EU AI Act and ISO/IEC 42001 reviews?
Identity, policy results, data handling, actions and outcomes are assembled into one reviewable record.
Support audits and compliance reviews with evidence already prepared
04Business owners
Is the agent improving revenue, service outcomes or productivity?
Completed work and exceptions are tied back to the business process the agent supports.
Scale the agents that create measurable business value
AI agent governance questions, answered.
How enterprises control agent identity, permissions, sensitive data, actions and evidence from sandbox to production.
AI agent governance is the system of identities, permissions, policies, data controls and audit evidence that determines what an agent may do and proves what it did. Difinity puts those controls in the execution path, so governance changes agent behaviour during a run instead of only reporting on it afterward.
Traditional AI governance often focuses on models, data, risk assessments and lifecycle oversight. AI agent governance must also control runtime authority: which systems and tools an agent can use, what data it can access, which actions it can take and when it must stop or escalate.
Enterprises control AI agents by giving each one a defined job, a distinct identity and least-privilege access to approved systems, data and actions. Difinity evaluates authority in context as the agent works, then blocks or routes anything outside the permissions and organisational policies that apply to that run.
Protect sensitive data before it reaches the agent or an external model. Difinity can detect and redact configured PII in the governed execution path and record which protections were applied. Coverage depends on the data paths and controls configured for that agent.
No. A governed agent can complete lower-risk actions autonomously within explicit boundaries. Difinity evaluates authority and policy at execution time, then routes exceptions or higher-risk actions to human review without allowing the agent to decide its own authority.
An AI agent audit trail should record the agent identity, assigned job, systems and data accessed, policies evaluated, actions attempted, blocks, fallbacks and final outcome. Difinity keeps these events in one accountable run record for investigation, review and compliance evidence.
Start with one bounded job in an isolated execution sandbox, limit network and system access, test policy outcomes and inspect the evidence from each run. Difinity lets teams expand an agent’s authority from observed behaviour instead of granting broad production access upfront.
AI agent governance can produce the traceability and operational evidence needed for regulatory and management-system reviews, but it does not by itself make an organisation compliant or certified. Difinity packages agent identity, policies, data handling, actions and outcomes into evidence that can support EU AI Act and ISO/IEC 42001 review workflows.
No. Difinity is designed for agents that act across approved enterprise systems and tools without replacing the systems of record they rely on. Teams can build and run agents on the platform while applying governance to the data and actions involved in each job.
Choose one job your agents
should be trusted to do.
Bring one workflow, the systems it touches and the actions the agent needs to take. See how Difinity can turn it into a governed run with control during execution and accountable evidence afterward.
Start with one bounded job, inspect the evidence, then expand from confidence.
