AI governance and compliance for systems that make or support decisions
We set up the controls around AI systems in use: who approves what, which data may be used, how decisions are logged, and what is written down for an auditor or a customer who asks.
The controls are built around the obligations that apply to your business and sector, which we confirm with you at the start.
Based in Lahore, we work with businesses across Pakistan and internationally.
Write down what the system may do, then make the system follow it
Governance is mostly documentation and a few technical controls that hold it in place. We start by listing the AI systems in use, what each one decides or influences, what data it reads, and who is accountable for it. From that list we agree which actions need a person's approval, what must be logged, and what the written policy has to say.
The controls are then built into the systems: approval steps, logging, access rules, and checks before release. The policy, the logs, and the test results are what you show when someone asks how the system is governed.
Quick answers
Which regulations apply to us?
That depends on your sector and where your customers are. We confirm the obligations with you and your advisers at the start; we do not assume a framework.
What gets logged?
Inputs, outputs, the decision or recommendation, who approved it where approval was needed, and the model version. The list is agreed per system.
Does this slow the system down?
Approval steps add time only where a person has to act, and those are chosen for the actions that carry risk. Logging runs alongside the system.
What a governance engagement can include
System inventory
List the AI systems in use, what each decides or influences, and who owns it.
Risk review
Rank the systems by the harm a wrong output could cause and the data involved.
Controls
Approval steps, access rules, logging, and release checks built into the systems.
Policy and documentation
Written policy for staff and a record of how each system is governed.
Review cycle
A schedule for re-testing the systems and updating the documentation.
Controls built into the systems you already run
Most controls are configuration and logging, with little new software. Where a system cannot log or gate an action, we say so, and the policy records the manual check that takes its place.
- Approval gates: Actions above an agreed risk level wait for a person
- Audit trail: Inputs, outputs, approvals, and model versions logged and kept
- Access rules: Who may use which system with which data
- Release checks: Tests run before a system or a model update goes live
Traceability
Privacy and safety
Standards
Compare two scenarios for time spent on reviews and audits of AI systems
Enter your own figures to compare the hours your team spends reviewing and documenting AI systems now with a second scenario you choose. This shows the arithmetic difference between the two; it does not forecast what a governance engagement will achieve.
These figures compare only the assumptions you enter. They do not include the cost of the engagement, and they do not predict time savings.
Inventory the systems
List what is in use, what it decides, and who owns it.
Confirm the obligations
Agree the rules that apply with you and your advisers.
Design the controls
Decide the approval steps, logs, access rules, and release checks per system.
Build and document
Put the controls in place and write the policy and the system records.
Review on a schedule
Re-test, update the documents, and report.
Who governance is for
Regulated sectors
Finance, healthcare, and others with reporting obligations on automated decisions.
Customer-facing AI
Assistants and agents whose outputs reach customers and need a record.
Teams using AI tools daily
Written rules for what may be entered into which tool.
Businesses supplying larger clients
Documentation to answer a client's due diligence questions.
Be able to answer the question when it is asked
Sooner or later someone asks how an AI decision was made, what data it used, and who approved it. Governance is having the answer written down and the logs to back it. The controls also catch the errors that would have become the question.
- Systems inventoried and ranked by risk
- Approval steps where the risk warrants them
- Logs kept for each decision
- Policy your team can follow
AI governance pricing
Our pricing page does not list a separate starting price for AI governance. Engagements are quoted after the inventory, based on the number of systems, the controls required, and the documentation in scope.
AI Governance and Compliance: your questions
Do you provide legal advice?
Can governance be added to a system already in use?
What does the written policy cover?
How often are systems reviewed?
How much does AI governance cost?
Do you work with businesses outside Lahore?
Tell us which systems you run
Describe the AI systems in use and who asks you about them. We will tell you what an inventory would cover and which controls are likely to be needed first.