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AI security evaluation and governance

Assessment follows the actual system boundary, authorised task and consequences of a failed control.

Discuss the programme family
Specialist engineering programme
Organisation boundaryRecordsOnsite modelReviewMission and domain requirements

Select the right programme within ai security evaluation and governance.

The programme family

Assessment follows the actual system boundary, authorised task and consequences of a failed control. Softinator connects specialist contribution to the engineering, information and operating requirements around the task.

Choose a focused engagement

The catalogue includes ai red teaming programmes, prompt injection resilience, agent tool security reviews, ai data privacy engineering, ai governance operating models. Each programme has its own contribution, artefacts and acceptance scope. Use the programme links below to identify the relevant engagement.

Commission the work

Bring the operating task, selected environment and result that matters. The engagement establishes scope, access, delivery responsibilities and the evidence used to assess the outcome. Connected platform and project pages provide the relevant context.

Choose the programme.

Agent tool security reviewsReview permission, execution and data paths in tool-using enterprise agents.AI audit evidence pipelinesMaintain reviewable evidence across model changes, releases and enterprise controls.AI data privacy engineeringApply project-specific minimisation and access boundaries to model workflows.AI governance operating modelsDefine practical ownership, review and release responsibilities for AI systems.AI identity and access integrationConnect model and agent access to enterprise identity systems.AI incident response preparationDefine diagnosis, containment and recovery workflows for AI system incidents.AI red teaming programmesAssess model and agent behaviour under task-relevant adversarial conditions.Compliance evidence integrationConnect control evidence to the enterprise procurement and assurance process.LLM application penetration testingAssess exploitable behaviour across applications, tools and model integration paths.Model risk assessmentAssess intended model use, evaluation coverage and operating consequences.Policy enforcement for agentsApply enterprise action constraints to agent execution and approval workflows.Prompt injection resilienceEvaluate and improve boundaries around untrusted inputs and tool actions.Responsible AI evaluationEvaluate behaviour against agreed use, inclusion and review criteria.Secure model supply chainsReview artefact provenance and dependency controls for model deployments.

Bring the next
requirement.

Discuss your programme