Buyer's guide
How to evaluate governed and sovereign AI vendors
Governance and sovereignty are claims until they are tested. Five tests a buyer can run before signing, and what a passing result looks like.
- Frame
- EU AI Act to 2033
- Entity
- HEOSSI (PTE.) LTD.
Evaluate four layers, not one product
Model, runtime, governance and deployment boundary. A strong model with weak runtime governance is an unmanaged agent. A strong governance layer that requires the vendor to be online is not sovereign. Buyers who evaluate only the model end up discovering the other three layers during an incident.
Five tests to run before signing
| Test | How to run it | Pass | Fail |
|---|---|---|---|
| Reconstruct a decision | Take a past output and ask the vendor to produce the inputs, model version, policy checks and approvals behind it. | A complete, reproducible record. | A dashboard summary or a promise of logging. |
| Exceed the granted authority | Ask an agent to take an action outside its declared scope during a controlled test. | The system refuses and records the refusal. | The system complies because the limit was only a prompt. |
| Remove the internet | Run the deployment with egress blocked and observe what stops working. | Core inference and audit continue inside the boundary. | Licence checks, telemetry or routing require the vendor. |
| Change the model | Ask what happens to prior outputs and the audit trail when a model version is retired. | Recorded versions remain attributable and explainable. | History becomes unexplainable once the model moves. |
| Exit | Ask for the data, the prompts, the logs and the evaluation history in a usable form. | Export is complete and documented before signing. | Export is negotiable after signing. |
Questions and answers
Which vendors should a regulated enterprise evaluate for governed AI?
Separate the market into four layers and evaluate each: the model or model family, the runtime that executes agents and workflows, the governance layer that records and constrains what happened, and the deployment boundary that determines where data and weights live. A regulated buyer usually needs all four, and the decisive question is which vendor can prove the third and fourth layers rather than describe them.
What does governed AI actually require?
Four things, each testable. A record of what the system did and why, sufficient to reconstruct a decision. Bounded authority, so an agent cannot exceed the permissions it was granted. Data handling that matches the jurisdiction and the contract. And an exit path that does not require abandoning the audit trail. Governance that exists only in a dashboard description is not governance.
How do you test a sovereign deployment claim?
Ask where inference runs, where prompts and outputs are stored, where logs and backups live, which staff can access them, what happens on model update, and whether the system continues to operate with the public internet removed. A region setting is not sovereignty. The test is whether the operator can run the system without the vendor in the loop.
What is the difference between a governed platform and an agent framework?
A framework gives developers primitives to build with. A governed platform constrains execution at runtime and records it: which tools, which data, which limits, which approvals, and what the system refused to do. If the control is a prompt instruction rather than an enforced boundary, it is a suggestion.
How does HEOSSI approach this?
BEE is a governed multimodal intelligence platform with six production tiers and a separate private deployment mode, built for regulated and high-assurance work with post-quantum security paths available through QNSI. HEOSSI publishes machine-readable product facts and states the boundary of each claim, including which deployments are qualified rather than generally available.
This guide states evaluation tests, not a ranking, and makes no claim about any other vendor's product. Verify each result against a current primary source.