PUT YOUR AI AGENTS TO THE TEST… BEFORE YOUR CUSTOMERS DO.
Before an AI agent touches your customers, your data, or your decisions, you should know it's ready. G·R·A·C·E is an evidence-based readiness assessment across five pillars covering not just the technical and governance risks, but the human ones: trust, judgement, and the edge cases where neat rules break down. Let's make your agents deployment-ready, together.
Introducing g.r.a.c.e
A practical guide for building and integrating AI agents within company workflows — covering not just the technical and governance dimensions of deployment, but the human ones: how people interact with agents, whether they trust them, and how context and judgment are handled at the edges of a workflow where neat rules break down.
Contact us to discover how we can apply our G.R.A.C.E. framework to your organisation.
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Governance - defines the organisational infrastructure that surrounds an agent. Without it, even a well-designed agent operates in a vacuum — there is no authority to approve changes, no named individual responsible when things go wrong, and no process to shut it down safely. Governance is not bureaucracy for its own sake; it is the foundation that makes everything else sustainable.
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Risk in agentic AI is multidimensional. It spans technical risk (hallucinations, adversarial inputs, dependency failures), operational risk (workflow disruption, compounding errors), reputational risk (customer harm, loss of confidence), and regulatory risk (compliance breach, data exposure). A risk-first approach surfaces these before deployment — not after — and maintains a living picture of risk as the agent and its environment evolve.
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Autonomy is not binary. It exists on a spectrum from fully supervised to fully autonomous, and the right level at any point in time depends on three things: the stakes of the workflow, the agent's demonstrated reliability, and — critically — whether the agent has sufficient contextual judgment to handle the full range of scenarios it will encounter. Granting autonomy faster than trust is earned is one of the most consistent failure patterns in agent deployment.
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Capability has two dimensions that must both be assessed before deployment. The first is technical: what can the agent do reliably, where does its performance degrade, and what are its known failure modes? The second is human: will the people working alongside this agent understand it well enough to use it correctly, trust it at the right level, and catch its errors before they propagate? Both dimensions are necessary. A technically capable agent deployed into an environment of miscalibrated trust will fail just as surely as one with poor underlying performance.
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Evaluation is the mechanism that closes the loop on everything else in the framework. Without it, governance decisions become stale, risk assessments lose relevance, autonomy levels are never revisited, and capability mismatches go undetected. Evaluation is not a one-time exercise at launch — it is the ongoing discipline that keeps the agent trustworthy, and the feedback mechanism that routes findings back into Governance, Risk, Autonomy, and Capability as the agent and its environment evolve.
Our Approach
Four ways to work with us, designed to build on each other; start with half-day introduction, go deep on a single agent, keep it trustworthy over time or embed the whole framework. Enter wherever you are on your agentic AI journey.
Half day
Half-Day Introduction
A grounded, hype-free introduction to governing AI agents. We cover why agents need more than traditional software governance, walk through the five G·R·A·C·E pillars, then run a live rapid assessment of up to three of your agents — risk-tiered, with the biggest gaps surfaced.
Per agent · 1–2 weeks
Facilitated Readiness Assessment
A deep, evidence-based verdict on whether a specific agent is ready to go live. We score all five pillars against evidence and run the four deep dives a checklist can't — grey-area nuance testing, trust calibration, red-teaming, and decision-rights mapping.
Recurring · quarterly or bi-annual
Ongoing Evaluation
Readiness is a point in time. We re-assess on a cadence that fits you — reviewing drift, re-running red-team tests, and feeding findings back into the framework, so your agents stay trustworthy as they and their environment change.
Programme
Full Framework Rollout
Embed G·R·A·C·E across the organisation — not one agent, but a repeatable operating model. We establish governance, ownership and policy, implement risk tiering and decision rights, train your teams, and build the framework into your deployment lifecycle.