AI governance
Govern what you automate.
AI governance is the confirm-step, access control, and audit trail that make an AI agent safe to act for your business. We build it in line with Singapore's IMDA Model AI Governance Framework and its direction on agentic AI, so an agent can act with permission and you can always see, and stop, what it did.
An agent that acts is a liability until it is governed.
An agent that can send a message, change a price, or move a record is doing real things in the world. Without governance, no one can say what it did, why, or on whose authority, and no one can stop it before it acts.
Governance is not a policy document written after the fact. It is the confirm-step, the access boundary, and the audit trail, designed into the system from the schema up, so autonomy and accountability arrive together.
Four parts, built in from the start.
Governance stopped being optional.
One register, every framework that applies.
Most businesses face more than one rulebook at once. Rather than a separate project per framework, we design a single governance register that maps the same controls to each obligation, so the work is done once and evidenced many times.
Capability, not certification: we design and document the governance system. The accountability is yours, and the evidence is built to stand up to a client's due diligence or a regulator's question.
Common questions.
What is AI governance for agentic systems?
It is the set of controls that make an AI agent safe to act for a business: an accountability register, owner confirmation before outbound actions, row-level access control, a full audit trail, and an incident runbook. It is designed into the system, not bolted on afterwards.
Do small businesses need AI governance?
Yes, in proportion. A small business running one governed agent still needs to confirm actions, control what the agent can reach, and keep a record. The controls scale down; the principle does not.
What is the IMDA Model AI Governance Framework?
It is Singapore's IMDA Model AI Governance Framework, including its 2024 guidance for generative AI, with IMDA extending its governance thinking toward agentic systems. We design our governance controls to align with it.
How does human-in-the-loop work in practice?
The agent prepares the action, a quote, a message, a change, and a human confirms before it goes out. For low-risk steps the boundary can be widened; for irreversible ones it stays tight. The owner decides where the line sits.
Is this compliant with PDPA and GDPR?
The approach is designed to align with PDPA and GDPR rules on automated decisions, including access control, audit, and the right to a human in the loop. We document how each control maps to the obligation so the alignment is evidenced, not just asserted.
Go deeper.
Make your AI governable.
Running agents, or about to? Let us design the governance before the autonomy. Real reply, no funnel.