Controls by design
Security and governance built into solution design.
AI Security & Governance
Design the security, governance and evaluation controls required for dependable production AI.
We help teams put guardrails around AI data access, review flows, model behaviour, vendor risk and post launch monitoring so systems remain safe and accountable in real business use.
Business first scoping
Clear outputs and next steps
Can continue into implementation
Human oversight
Approval paths and review queues where they matter.
Auditable operation
Trace what the system accessed, generated and did.
Ongoing evaluation
Monitor performance, drift, quality and misuse risks.
The business problem
Production AI needs more than model access, it needs control.
If a system can access knowledge, trigger workflows or influence decisions, teams need clear rules around identity, permissions, approvals, testing and monitoring. We design these controls to fit the workflow instead of slowing it unnecessarily.
What this service changes: it converts an unclear opportunity into a structured, reviewable path with clear decisions, owners and outputs.
What we do
Focused capabilities that move the service from discussion to action.
Each capability addresses a specific decision, dependency or delivery need. Use them independently or combine them into one complete engagement.
01
Access and permission design
Control who can access data, tools, prompts and outputs.
02
Risk and threat review
Assess prompt injection, leakage, misuse and third party risks.
03
Evaluation framework
Define test sets, acceptance criteria and release gates.
04
Human in the loop design
Specify who reviews what and under which conditions.
05
Governance documentation
Document controls, operating policies and accountability.
06
Monitoring and audit
Track output quality, system actions and operational events after launch.
How the service comes together
A control framework that supports safe delivery and dependable operation.
The sequence creates visible decision points so your team knows what has been learned, what has been approved and what happens next.
- 01 Review data and workflow risk
- 02 Design control model
- 03 Define evaluation gates
- 04 Embed monitoring and audit
- 05 Operationalise governance
What you receive
Decision ready outputs your team can use immediately.
The engagement produces practical artefacts, not only discussion. Outputs are structured to support approval, implementation and handover.
Output 01
AI governance checklist
Output 02
Security and control recommendations
Output 03
Evaluation scorecard
Output 04
Human review design
Output 05
Policy and documentation set
Output 06
Monitoring requirements
Delivery approach
Progress through visible decisions and working increments.
The exact timeline depends on scope, data and integrations. Every engagement is organised around evidence, review points and production readiness.
-
01
Risk review
Understand goals, constraints and the current operating context.
-
02
Control design
Define the solution direction, priorities and success measures.
-
03
Evaluation planning
Produce and review the agreed working outputs with stakeholders.
-
04
Operational handover
Confirm handover, next phase actions and production readiness.
Related delivery evidence
Recruitment Automation Platform
Simplify Job Search was developed as a two sided job search and hiring platform that supports both candidates and recruiters. This case study focuses on the recruitment side platform, which helps HR teams, companies, freelancer recruiters,…
Read the case studySecurity and responsible operation
Controls and quality checks are designed into the engagement.
We adapt governance, review and operational controls to the service, workflow, users and level of risk involved.
- Role based access design
- Output and action approval controls
- Vendor and credential governance
- Post launch monitoring and incident readiness
Frequently asked questions
Questions teams ask before getting started.
Every engagement is shaped around the workflow, data, security and operating environment involved.
Can governance be lightweight for a small pilot?
Yes. Controls should match the level of risk and business impact. We right size the approach.
Do you help with vendor and model risk reviews?
Yes. We can assess hosted models, providers, dependencies and data handling implications.
How do you handle evaluation?
We define test cases, quality checks and release criteria specific to the workflow and risk level.
Can you work with internal security or compliance teams?
Absolutely. We often collaborate directly with enterprise security, legal and compliance stakeholders.
Start with the real requirement
Bring us the workflow, product or system you want to improve.
We will help identify the most practical first phase and the capabilities required to deliver it well.