Is this a policy document or an operating model?

An operating model. A policy nobody can execute is the most common artifact we are asked to replace.

Do you cover the licensing changes vendors are attaching to agents?

Yes — platform vendors have begun gating agent security and governance features behind specific licences. We review what your current entitlements actually cover before you commit to a deployment model.

Can you run this for agents another firm built?

Yes. Governance and post-deployment support don't require DataMap to have built the original.

Governance & operations

The layer that decides whether your second AI use case ever ships

Responsible-AI governance, compliance evidence, and post-deployment optimization and support. Our engineers hold privileged access to clients' Coupa, SAP, and Dynamics environments, so we run on audited controls — SOC 2 completed with zero exceptions.

Talk about AI governance

Governance, risk & scaling

Pilots are ungoverned by definition. Production can't be.

The move from one agent run by the team that built it to a fleet of them run by the business is a governance change, not a technical one. Access, evaluation, cost, audit, and rollback all have to have owners.

Governance

Policy that an auditor and an engineer can both use

An operating model for who may deploy an agent, what data it may reach, which actions require a human, and how a change gets approved — written so it survives an audit and still lets people ship.

Agent registry and ownership model
Data-access and action-authorization policy
Change approval and rollback procedure

Risk & compliance

Evidence, not assurances

Audit logging, evaluation results retained over time, and the documentation your compliance function needs — including the platform-licensing and security requirements vendors now attach to agent deployments.

Auditable action logs
Retained evaluation and drift evidence
Platform security and licensing review

Two hands completing an agreement with a blue pen

Scaling

Optimization and support after go-live

Cost and latency tuning, prompt and grounding maintenance as the underlying platforms release, and the same weekly support cadence we run for production systems.