Guide
How to evaluate an AI governance platform
Vendors in this category all use the same words. The questions that show what a product does on discovery, enforcement, agents, frameworks, evidence and cost.
How should we evaluate an AI governance platform?
Evaluate against questions that expose what a product actually does rather than what its feature list claims, because the category's vocabulary has converged while the products have not. The questions that separate products fastest are these. Does discovery correlate real signals from identity, device, cloud and network sources or rely on self-reporting? Does enforcement act on live traffic or is it approval workflow? Does agent governance limit what an agent may do while it runs or only record what it is? Is the framework content you need actually loaded as usable data? Can a third party check the audit trail without access to the vendor's systems? And can your organisation buy and start without a long enterprise sales process? Ask every vendor the same questions and make them show you rather than tell you.
Every vendor in this category claims discovery, assessment, enforcement, monitoring and audit. The words have converged because the analyst category has, but underneath the words are three different product lineages with different strengths, and a feature checklist cannot tell them apart. Questions can. This guide sets out the ones that expose the differences fastest, and they work on any vendor, including Aicura.
On discovery: signals or self-reporting?
Ask the vendor to name the sources their discovery actually reads, and to show a finding traced from the original signal to the register. Discovery ranges from a form teams fill in, to scans of a single source, to correlation across identity providers, device management, outbound network traffic, cloud inventories and finance systems. The width matters because shadow AI does not announce itself in any single source, and the correlation matters because raw hits without resolution just move the work. Ask what share of findings in a reference deployment came from sources other than self-reporting.
On enforcement: does it act on traffic, or on paperwork?
Ask what happens to a prompt that violates policy at 2pm on a Tuesday. For most of the category the answer, once unwound, is that nothing happens to the prompt, because “enforcement” means an approval workflow that ran before deployment or a review task created after the fact. Real enforcement on live traffic sits between your people or systems and the AI model, and blocks, redacts or constrains the request itself. Both models are legitimate, but they are different products, and a vendor should be able to say plainly which one they are. Follow up by asking to see an enforcement event fire live, and where the record of it lands.
On agents: is the governance a record or a constraint?
Ask whether the platform can stop an agent doing something, or only record that it did. Agent registries are now common. Limits on which tools an agent may call and what it may do while it runs, suspension of a misbehaving agent and a decision log of what an agent actually did are much rarer, and they are what the risk of systems that act calls for. Ask to see an agent’s permitted tools changed and the change take effect, and ask what record exists when someone later asks why an agent did something.
On frameworks: loaded data or a logo wall?
For the frameworks you need, ask to see the content operating inside the product, not the logo on the website. Framework coverage claims range from content genuinely wired into assessments and reviews, to mappings maintained on request, to a list. The question bites hardest outside the EU and the US, because much of the category’s content was written for those two and national frameworks elsewhere are often thin or missing. Ask to see an assessment run against the framework that matters to you, on your systems.
On evidence: who has to be trusted for it to hold?
Ask whether a third party can check the audit trail without access to the vendor’s systems. The category’s standard words here are immutable, tamper-evident and system of record, and they almost always describe an append-only log inside the vendor’s own infrastructure. That is a promise about the vendor’s database, and relying on it means trusting the vendor. Cryptographically verifiable evidence is different in kind, using hashes anchored externally, timestamps from an external service, signatures with external keys and a verifier the third party can run themselves. If a vendor’s answer is a description of access controls, you have your answer. The companion guide on what makes AI evidence independently verifiable covers the distinction in full.
Then ask the continuity version. If the vendor disappears in five years, what happens to your evidence? The answer reveals whether the record’s durability depends on the vendor’s survival.
On buying: can you start, or only be sold to?
Ask what the smallest real commitment is, and whether you can make it without a sales process. Much of the category is sold only through an enterprise sales process, with entry prices set for large organisations. That is a fine model for some buyers and a wall for others. A free or low-floor entry means the evaluation can be your own hands on your own systems rather than a scripted presentation, which improves every other question on this list.
Running the evaluation
Ask every vendor the same questions, in writing, and make the shortlist show rather than describe. One real piece of work end to end beats any presentation, so register real systems, run a real assessment against your real framework, fire a real guardrail, produce a real evidence pack and hand it to someone sceptical. Where a vendor is weak, listen for whether they say so plainly. A vendor who concedes a real limitation and explains the mitigation is telling you more about the next five years of the relationship than one who has no weaknesses at all. Before any of that, know your own starting point. A maturity assessment shows which of the seven areas you are weakest in, which is where the evaluation should press hardest.
Where Aicura fits
Run these questions against Aicura the same way you would against anyone else. The discovery question can be tested on the free Register tier with your own sources connected, by checking which AI tools discovery reports and how each one reaches the register. The framework question has a plain answer by plan and country. Privacy carries your country’s rules on automated decisions. Essentials adds national frameworks, such as the EU AI Act in the EU or Australia’s Guidance for AI Adoption. Pro adds ISO/IEC 42001, the NIST AI RMF and sector and breach notification frameworks. Your country’s pricing page lists them. Enforcement, agent limits and the Evidence Vault, Aicura’s sealed store of evidence snapshots, are Pro capabilities, and for those the proof of concept starts with a conversation.
Aicura provides guidance, not legal advice, and does not certify or audit. It issues no compliance verdicts or scores by design, so if your evaluation requires a product that asserts pass or fail, that is a real difference to weigh, and we would rather say so here than surprise you in month three.
A note on this page
This guide is written by a vendor in the category it describes, so read it the way you would read any vendor’s evaluation advice, as a set of questions to ask everyone, us included. It is general information, not advice, and the right weighting of these questions depends on your organisation’s obligations and risk.
Questions
Should we shortlist AI governance platforms from an analyst quadrant?
Quadrants are useful for drawing the category boundary and knowing who is in scope. They are less useful for fit, because placement rewards scale and breadth while your decision turns on depth in the two or three areas your organisation actually needs. Use the analyst view to build the longlist and these questions to cut it.
What should an AI governance platform proof of concept prove?
One real piece of work end to end, with your systems and your people. Register real systems, run a real assessment, fire a real guardrail and produce a real evidence pack. A scripted presentation on the vendor's data proves only that the script works.
What if a vendor answers every question well?
Be more suspicious, not less. The lineages are real, and depth everywhere is not how this category has developed. Press hardest on the areas furthest from the vendor's origin, and ask them to show rather than describe.
How does Aicura answer these questions?
Discovery reads identity, device, cloud, IT service management, code and workspace sources, and a person decides whether each AI tool it reports is added, linked or ignored. Enforcement acts on live traffic, through gateways in your environment that run signed sets of guardrail rules, and every block, redaction and escalation is recorded. Agents sit in one register with systems, with limits on the tools they may call that apply while they run. Framework content is loaded as data and tiered by plan. Evidence snapshots are sealed so anyone they are shared with can confirm they have not changed. And a free Register tier with self-serve plans above it lets you try discovery and the register on your own systems before you talk to anyone.
Start with the AI you run
Aicura's AI register and discovery are free to start. Find the AI in your organisation and give every system an owner.
