A scripted demo is not due diligence.
A demonstration shows the path you intended. Enterprise buyers need to know what happens off that path, with their data, their users and their misuse in view.
Services /AI Product
AI Product
Assurance
Give enterprise buyers a clearer view of your product’s behaviour, risks and controls.
Discuss an AI productBuild confidence in your product.
Enterprise customers need to understand what happens when your product meets their data, users and workflows. Independent testing helps you identify weaknesses and gives buyers a substantive basis for evaluating your product.
Product assurance is independent testing of an AI product before a customer relies on it, or before that product goes through enterprise due diligence. We look at the release you are taking to market: how it behaves with a customer’s data and users in mind, how tenants are separated, what its agents are allowed to do, and whether the controls you describe are the controls the product enforces.
Buyers are rarely short of a questionnaire. They are often short of evidence that the answers match the build. The engagement produces that evidence for a defined release and a defined buyer conversation. It is not a certification, and it does not promise that every future configuration will behave the same way.
What a demonstration
does not show.
Tenant boundaries are a procurement question.
Isolation, retention and what one customer can cause another customer’s agent to see are decided in architecture, then asked about in security review.
Agent permissions are hard to explain later.
If the product can call tools or act in a customer’s systems, buyers will ask who can authorise an action and how that limit is enforced, not only described.
Questionnaires drift from the release.
Answers prepared for a sales or compliance process go stale when prompts, indexes, models or permissions change and nobody retests the claim.
System-specific.
Evidence-led.
- 01Product architecture and attack surfacesHow the product is put together, where untrusted input enters, and which components can reach customer data or customer systems.
- 02Prompt injection, jailbreaks and tool abuseWhether adversarial instructions, in direct use or in content the product reads, can override controls or drive tools outside their role.
- 03Tenant isolation and data handlingWhether one customer’s data, prompts or actions can affect another, and how retention and access are actually implemented.
- 04Reliability under realistic use and misuseHow the product behaves on representative customer tasks, including incomplete, ambiguous and hostile inputs.
- 05Agent permissions and escalation pathsWhat an agent can do without a person, how privilege is granted, and when a human is required to approve or stop an action.
- 06Customer-facing controls and documentationWhether the security, privacy and administration claims a buyer will read match the behaviour of the release under test.
A clear path
through assurance.
01
Define the product and the buyer question.
We agree the release, the deployment model, the claims under test and the decisions the evidence needs to support.
Independent evidence for enterprise conversations.
- Product assurance reportFindings and their significance for the release, written for both the team building the product and the buyer reviewing it.
- Technical testing resultsWhat was attempted, how the product was configured, and what it did, including tests that did not produce a weakness.
- Prioritised risk findingsIssues ordered by the consequence for an enterprise customer, separated from observations that need more evidence.
- Reproducible testing evidenceEnough detail for your engineers to recreate the condition and confirm a fix, without handing a buyer a raw working note.
- Remediation recommendationsChanges to product behaviour, permissions, isolation, logging or documentation, each tied to a finding.
- Scoped independent assurance statementA statement of what the engagement covered and what it supports. It is explicit about scope so it is not read as a general approval.
Deliverables and testing scope are agreed at the start of the engagement.
Evidence a buyer
can actually use.
A report that can sit in a security review.
Procurement and security teams receive an account of behaviour and limits, rather than a feature list or a completed questionnaire on its own.
Findings your engineers can reproduce.
Each technical issue is described well enough to recreate, fix and, where agreed, retest against the same condition.
A clearer account of the release.
Tenant isolation, tool permissions and failure modes are described for the build under test, not for the product in the abstract.
A statement with a boundary.
The assurance statement says what was in scope. A buyer can use it without mistaking it for a certification of every future configuration.
Built around
your responsibility.
Enterprise AI vendors, AI SaaS companies, vertical AI platforms and agent developers preparing for customer due diligence or a significant product release.
- 01A customer has started due diligence.Security and procurement have asked how the product behaves with their data, and a demo plus a standard questionnaire is no longer enough.
- 02A release changes what the product can do.A new agent, tool, integration or model is about to ship, and the previous assurance no longer describes it.
- 03You need an independent view before you claim one.The team wants weaknesses found, and documented, before a buyer finds them in a pilot.
Where this sits.
If a customer is deploying your product inside their own environment, deployment assurance is the brief on their side of the work. Deployment support helps while an implementation is still being designed. Continuous assurance stays with a product that keeps changing after release.
01
AI Deployment Assurance
Independent testing before AI enters your organisation’s workflows, data and decisions.
03AI Deployment Support
Independent guidance and testing alongside your team throughout implementation.
04Continuous AI Assurance
Ongoing testing as models, prompts, integrations and permissions evolve.
Deploy AI with confidence.
Start a conversation about your system, what it needs to do and what you need to know.