Responsible AI
AI that enterprises can trust.
AI systems must be designed not only to be intelligent, but also secure, controllable, observable and accountable. We take a risk-based approach to governance rather than a one-size-fits-all checklist.
Human oversight by design
AI agents are given clearly scoped permissions. Actions with meaningful business, financial or legal impact are routed through a human approval step rather than executed autonomously.
Evaluated before deployment
Agents are evaluated for accuracy, reliability, safety, latency and cost against the specific workflow they're built for — not a generic benchmark — before they touch production data or systems.
Access control and least privilege
Agents are granted the minimum system and data access required to perform their task, with permissions and identity managed the same way as any other enterprise system integration.
Auditability
Agent decisions, tool calls and escalations are logged so that actions can be reviewed, audited and explained after the fact.
Security testing
Agent-facing surfaces — including prompt injection and tool-misuse paths — are tested as part of the build and evaluation process, not treated as an afterthought.
Risk-based governance
Not every agent carries the same risk. Governance controls — approval gates, monitoring depth, escalation procedures — scale with the impact of what the agent is allowed to do.
Areas covered
Depending on the engagement, our governance approach addresses the following areas. We do not claim certifications the company does not formally hold.