Security & compliance
Trust is built into the architecture
Data flows, privacy requirements and effective control belong in the design of an enterprise AI deployment, before access to sensitive information.
Our approach
Hunter BI treats security as part of an AI deployment's acceptance criteria: the team must understand data flows, permitted actions, provider terms and the evidence needed for review. Cloud, on-premise and sovereign options are assessed against the project. The applicable controls and responsibilities are documented and tested; a product label or partner badge does not establish compliance.
Four areas to examine before production
Data location
Map model requests, storage, connectors and logs before selecting a deployment architecture.
Confidentiality
Classify information and verify the terms and settings of the actual service and account.
Traceability
Define useful evidence, authorised access and retention without creating unnecessary copies of sensitive data.
Human control
Separate preparation from execution and require approval for consequential business actions.
Data residence and sovereignty: examine the complete path
Before a pilot, identify where information is sent, which services process it and who can inspect the resulting records. The location of a workstation or MCP server alone does not establish where model processing, backups or telemetry occur. A diagram should include the connected applications as well as the model.
Deployment options can include a managed cloud service, models operated within your infrastructure or a specifically scoped hybrid arrangement. For sensitive environments, isolation requirements affect network access, updates, monitoring and support. These choices must be tested against the actual task and operating capability, not selected solely because an architecture is described as sovereign.
Define what happens when an external service is unavailable and which tasks must stop. Do not silently send restricted information to another provider. The delivery record should make the permitted processing boundary and its unresolved points visible to the responsible team.
Explore sovereign AI deploymentPrivacy and compliance: document the applicable conditions
Start with the purpose of each use case, the information required and the people authorised to use it. Data classification precedes connection to an assistant. Client contracts, sector requirements and the organisation's own policies may restrict a workflow even when a software feature is technically available.
For projects involving Morocco, review applicable personal-data requirements, including Law 09-08 and CNDP procedures, with the responsible legal and data-protection specialists. European data flows may require a separate GDPR assessment. This page does not determine the legal basis, required formalities or compliance status of a particular project.
Check provider commitments for the chosen plan and configuration. Training use, storage, retention, access and transfer conditions are separate questions. Record the applicable agreement rather than assuming that every enterprise-labelled product has identical terms. Where required, prepare the processing agreement, responsibilities and evidence before authorising real data.
Explore AI governanceAn audit trail that is useful and proportionate
Agree which sensitive operations need records: the requested action, relevant source references, output, approval and execution result may be necessary depending on the workflow. Define who can consult those records and how long they remain available. Logging everything indefinitely can introduce another sensitive-data store.
A system should distinguish a supported answer from one that lacks sufficient information. It should also distinguish a prepared change, an approved action, an attempted execution and a verified result. These states must not be collapsed into a generic success message that hides uncertainty.
The delivery package should include tested access restrictions, important error cases, operational owners and a suspension procedure. Changes to a connector, model or application can require targeted regression checks. Support commitments, access to evidence and retention responsibilities belong in the agreed scope, not in an assumed universal guarantee.
See how controls apply to MCP integrationsHuman approval and clear limits
Define the agent's permitted actions explicitly. Reading approved information, drafting a message and sending it are different authorities. A write action needs an exact target, intended content and the required approval. After execution, verify the recorded outcome before reporting completion or retrying an uncertain request.
Hunter BI does not claim an unheld certification or a productivity percentage that has not been measured. Participation in the OpenAI and Anthropic partner networks is separate from a project's security assessment. Referencing ISO/IEC 42001 as a governance framework is not a claim of certification.
A pilot can be restricted, postponed or rejected when necessary controls are unavailable. The objective is a decision supported by evidence that your technical, business and risk owners can examine. Preparing that evidence supports their review; it does not replace their accountability or a required independent audit.
Read the coding-agent security checklistDiscuss your AI security requirements
Scope the data, permitted workflows, responsible owners and evidence needed before a pilot.
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