Agents Stack finds the AI already running in your business, classifies what each use case puts at risk, and builds the oversight you can evidence to an executive team, an auditor or a regulator.
A defined assessment with an agreed scope and a dated report. Not an open-ended advisory retainer.
Works with the identity, cloud, data and GRC platforms already in place. No wholesale rip and replace.
The inventory, risk positions and evidence pack are yours to keep, and can be credited against subsequent delivery.
AI enters an organization faster than governance does. By the time anyone asks for an inventory, the estate already spans approved platforms, embedded vendor features, team-level tools and a growing number of agents acting on real systems.
No single view of which AI applications, models and agents are in use, who owns them, or what data they touch.
Use cases approved at different thresholds by different teams, with no consistent measure of impact or autonomy.
Agents granted standing permissions with no defined authority boundary, escalation path or safe shutdown.
Policies that exist on paper while the evidence behind them is reconstructed by hand before each audit.
Supplier AI capability switched on by default, with no assurance position on the model or the data behind it.
Boards asked to accept AI risk they have no instrumented way to see.
Discover approved, emerging and unapproved AI use, including shadow AI and vendor features already switched on. Connect each application, model and agent to its business purpose, accountable owner, data, users and the decisions it affects.
Classify each use case on impact, autonomy, data sensitivity, regulatory relevance and potential consequence. Higher-risk uses earn deeper assessment, testing and approval. Lower-risk uses follow a streamlined path rather than stalling in a queue.
Define each agent's identity, purpose, owner, permissions, tools, knowledge sources and prohibited actions. Set confidence thresholds, approval gates, transaction limits, escalation conditions and safe shutdown before anything reaches production.
Map your AI principles and policies to the standards and obligations you report against, so a change in requirement traces straight through to the use cases, controls, suppliers and approvals it affects.
Lead with a measurable business problem, establish the baseline, and expand only once outcomes, governance and adoption are established.
Confirm the business outcome, scope, risk appetite, stakeholders, obligations and success measures. You leave this stage with shared priorities and clear decision rights.
Establish the current-state baseline across AI use, governance maturity and priority controls. You leave this stage with evidence-based gaps, quick wins and dependencies.
Define the target operating model, policy set, agent authority model and reporting line. You leave this stage with a deployable plan that has human oversight built in.
Assessments are mapped to the frameworks and sector obligations that apply in your jurisdiction.
A fixed-scope assessment that establishes the baseline, identifies material gaps and quick wins, and gives you a roadmap you can take to the board. Findings are retained by you and can be credited against subsequent delivery.
