01
Plug agents in
Generate an API key or install the official n8n node. Any agent framework — Claude, LangChain, custom code, n8n workflows — can start reading and writing within minutes.
Agentic GRC
Agentic GRC
Agents can do real GRC work — drafting controls, assessing vendors, triaging findings, completing recurring tasks. But only if the platform beneath them is built for it. Kordon is API-first, fully connected, and schema-extensible by design — the same substrate behind GRC engineering.
Definition
What agentic GRC means
Agentic GRC is a way of running a governance, risk and compliance programme where AI agents carry out defined pieces of the work — drafting a control, assessing a vendor, triaging a finding, closing a recurring task — and a person approves the parts that carry consequence.
The word doing the work there is defined. An agent needs a scope it cannot exceed, context it can read without being handed it, and a record of everything it changed. Those are properties of the platform underneath rather than of the model on top, which is why two products can both claim agentic GRC and mean very different things by it.
How it works
From API key to agent-run ISMS in four steps
Kordon doesn't bolt AI onto GRC. It gives you a structured, addressable, fully-connected platform that agents — yours, ours, or third-party — can operate against with confidence.
02
Let agents populate the ISMS
Turn unstructured input — meeting notes, vendor questionnaires, ticket exports — into connected assets, risks, controls, and requirement mappings. Agents do the translation; you review the result.
03
Automate the recurring work
Vendor reviews, control description updates, finding triage, evidence collection, task completion. Agents handle the repeatable parts of running a security program while humans focus on judgment calls.
04
Keep humans in the loop
Agents propose; humans approve. Assign agent-drafted work for review, require sign-off on high-impact changes, and use Kordon's permissions model to scope exactly what agents are allowed to do.
Built for agents
A platform agents can actually operate
Agentic GRC isn't about AI-generated checkboxes. It's about agents doing real work — reading context, making connections, updating state, and leaving an audit trail. Kordon's architecture makes that possible.
Complete REST API coverage
Every action available in the Kordon UI is available through the API. Risks, controls, tasks, assets, vendors, findings, connections, custom fields — all readable, writable, and automatable. No hidden surface area.
Official n8n node
Orchestrate multi-step agent workflows visually. Trigger actions in Kordon from external events, or chain agent reasoning steps across your tools. Full parity with the API — the same complete object model.
Connected object model
Risks, controls, assets, vendors, business processes, requirements, findings — everything connects to everything. Agents can reason across the mesh instead of dealing with flat, disconnected records.
Custom fields that behave natively
Agents can extend the schema with typed custom fields that look and work exactly like built-in ones. Capture exactly the context your agents need without waiting on a vendor roadmap.
Tasks, evidence, and health
Agents don't just create records — they complete recurring tasks, attach evidence, and trigger health propagation across assets, vendors, and processes. The platform computes state; agents operate on it.
Audit-ready traceability
Every create, update, and completion is attributable and timestamped. Agent-driven changes flow through the same controls as human changes, with the same audit trail auditors already trust.
Where the lines fall
Traditional, copilot, agentic
The same vocabulary gets attached to products that work in genuinely different ways. This is the distinction that matters when you are evaluating one.
| Traditional GRC | AI copilot | Agentic GRC | |
|---|---|---|---|
| Who does the work | A person, in the interface | A person, working from suggested text | An agent, inside a scope you set |
| What the AI produces | Nothing | Wording for a human to accept or reject | Changes to records, tasks and state |
| Where context comes from | Whatever the person remembers to look up | Whatever fits in the prompt | The platform's connected object model |
| How work gets reviewed | Peer review, when there is time for it | The person edits before saving | Approval before high-impact changes commit |
| What the auditor sees | Manual edit history | Manual edit history | The same attributable, timestamped trail as human work |
| What it asks of the platform | A usable interface | A text field and a model | Full API coverage, connected objects, scoped permissions |
Common questions
Agentic GRC, answered
What is a GRC AI agent?
A GRC AI agent is a program that reads context from your GRC platform and changes something in it — drafting a control description, pulling a vendor assessment together, triaging an incoming finding, completing a recurring task and attaching the evidence. What separates it from a chatbot is that it acts on records rather than producing text for someone else to paste in. What separates it from an unsupervised script is that its permissions are scoped and its work is reviewable.
How is agentic GRC different from traditional GRC software?
Traditional GRC software waits for a person to do every piece of work through the interface. An AI copilot drafts wording that a person still has to act on. Agentic GRC gives agents a defined scope to work inside, and routes the consequential decisions to a human for approval. The practical difference sits in the platform: agents need complete API coverage, objects that connect to each other, and a permissions model that can constrain them.
Is agentic GRC auditable?
It is auditable when agent activity runs through the same controls as human activity. In Kordon, every create, update and completion is attributable and timestamped whether a person or an agent did it, so an auditor reviews one trail rather than reconciling two. Agents are scoped through the same permissions model as users, and high-impact changes can be routed for sign-off before they commit.
Does agentic GRC work with ISO 27001, NIS2 and E-ITS?
Yes. Kordon's framework coverage is ISO 27001, NIS2 and E-ITS rather than SOC 2 alone, and agents operate on the same requirement mappings and control objects the frameworks are modelled in. This matters for European and regulated organisations, where much of what has to be satisfied is organisational — risk assessments, approvals, vendor reviews, management sign-off — rather than infrastructure configuration a scanner could check.
Do I have to build the agents myself?
No, though you can. Kordon exposes a complete REST API and publishes an official n8n node, so you can wire agent workflows visually without writing code, script directly against the API, or point an existing agent framework at it. The platform's job is to be operable; which agents you point at it is your choice.
Can agents run against an on-premises deployment?
Yes. Kordon's on-premises deployment exposes the same API and object model as the hosted version, so agent workflows work identically where data residency or sovereignty rules keep your ISMS inside your own infrastructure. This is a genuine gap in most agentic GRC tooling, which assumes a cloud-native estate.