Tool-connected agents
The agent can send, change, create, or trigger actions.
Services
AI governance and security
Put AI agents under control before they reach critical data and tools
We define who can do what, with which data, approvals, and evidence. Each system becomes observable, testable, and reversible according to its risk level.
Rules business and technical teams can operate
- Clear ownershipEach use case has an owner, validators, and escalation path.
- Minimal accessThe agent receives only the data and tools required for its task.
- Tested qualityAn evaluation set covers expected answers, edge cases, and refusals.
- Traceable actionsImportant decisions and tool calls are logged for review.
Deliverables
Controls around an AI system
Controls are matched to the use case instead of applying one checklist to every project.
System inventory and risk classification
Roles, permissions, and approvals
Data retention and deletion rules
Quality, security, and robustness tests
Logs, alerts, and incident procedure
Governance plan and review calendar
Use cases
When governance becomes a priority
Confidential data
Sources include customer, HR, financial, or contractual data.
Impactful decisions
Outputs affect a person, payment, compliance duty, or critical operation.
Method resource
AI audit: risk, compliance, and performance
Our guide connects practical controls with NIST AI RMF, ISO 42001, and context-specific obligations.
Review the evidence and context4
NIST AI RMF functions
3
control layers
1
owner per system
How we launch your first AI system
01
Scope
We choose one concrete use case: customer chatbot, internal assistant, or business automation.
02
Build
We create the prototype, prompts, workflows, guardrails, and required integrations.
03
Connect
We connect the agent to your documents, CRM, forms, emails, tickets, or APIs.
04
Improve
We observe real usage, correct answers, measure gains, and prepare the next use case.
FAQ
AI governance questions
Do we need ISO 42001 for the first project?
Not always. The framework can guide controls without immediately starting a full certification program.
How is prompt injection addressed?
Through instruction-data separation, least privilege, input and output validation, tool limits, monitoring, and adversarial tests.
Who validates outputs?
It depends on impact. Low-risk outputs can be sampled; sensitive actions require approval before execution.
Does governance slow delivery?
Proportionate controls prevent late rework. Critical safeguards are designed in, then strengthened with usage.
Launch a useful AI agent, not a vague project
Describe your need. We help you choose the first AI system to build: chatbot, internal assistant, or business automation.