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Trust & Security

Procurement-ready AI delivery without inflated security claims.

TeqEngine helps you understand how an AI system will handle data, permissions, model dependencies, evals, observability, and rollout risk before implementation work becomes expensive.

Data Handling

  • Client data stays inside approved project systems and client-authorized environments.
  • No client data is used to train public models by TeqEngine.
  • Retention, deletion, and access rules are defined during engagement scoping.

Access Control

  • Least-privilege access is used for repositories, cloud accounts, model providers, and data stores.
  • Privileged access, secrets, and service credentials are handled through client-approved tooling.
  • Human review and approval gates are designed for high-impact agent actions.

Deployment Boundaries

  • Systems can be built in client cloud, TeqEngine-managed cloud, or a jointly approved environment.
  • Production changes ship with rollback, logging, and operational ownership defined.
  • Vendor and model choices are documented with portability and dependency risk in mind.

AI-Specific Controls

  • Eval harnesses, traces, and failure taxonomies are designed before broad rollout.
  • Tool use, retrieval, model routing, and agent permissions are treated as security boundaries.
  • Prompt-injection, data leakage, hallucination, cost, latency, and escalation paths are reviewed.
Procurement Assets

The artifacts your stakeholders need before sign-off

These assets can be produced during a diagnostic or attached to an implementation proposal so security, finance, and technical stakeholders have the same operating picture.

Security questionnaire responses
Architecture and data-flow diagrams
AI risk register and mitigation plan
Model, vendor, and dependency inventory
Access-control and auditability summary
Implementation roadmap and SOW-ready scope
Review Rhythm

Trust work is built into the delivery path.

Before kickoff

Confirm data classes, access model, cloud environment, model providers, review requirements, and procurement constraints.

During diagnostic

Produce the architecture, data-flow, eval, observability, and risk artifacts your stakeholders need to approve the work.

Before production

Validate rollout gates, incident paths, human oversight, monitoring, cost controls, and rollback ownership.

Ready to discuss your project?

Start with a 2-week diagnostic to get a clear architecture plan.