AI governance framework
AI Governance That Works Inside the Workflow
Core controls
Six layers of governance, built in
Not add-ons - these controls are part of the IGNA operating model.
Approved Data Only
Agents connect only to vetted, role-approved data sources. No hallucination from unauthorized content.
Role-Based Access
Every agent interaction is scoped to the user's role, department, and approved knowledge boundaries.
Human Review
High-impact decisions are routed to human reviewers with full context before any action is taken.
Audit Trails
Every interaction, decision, and escalation is logged with context, user, and outcome for compliance review.
Escalation Rules
Defined escalation paths ensure exceptions and edge cases reach the right person automatically.
Observability
Live dashboards track usage, accuracy, unresolved topics, and risk signals across all deployed agents.
C.A.S.E. quality standard
C.A.S.E. – The four tests every agent must pass before it goes live.
C.A.S.E. is the answer to the question every responsible buyer asks: "How do we know the AI is doing what we said it would do?" Before IGNA deploys an agent, it is reviewed against four requirements.
C
Connect
The agent is connected only to trusted, approved, traceable data sources.
A
Align
The agent stays within the organization's policies, goals, and approved scope
S
Structure
Workflow, escalation path, and human review points are designed upfront - not improvised.
E
Evaluate
Accuracy, usage, risk, unresolved topics, and value are measured continuously after go-live.
CFO
Governance standard that reduces financial and operational risk before any agent goes live.
CIO
Clear data, integration, access, and audit expectations before any production deployment.
COO
Agents are structured around real workflows, not model improvisation or open-ended exploration.
Compliance
Approved data, scope, review paths, and evaluation before go-live - auditable at every stage.
AI Policy + Agent Readiness
Define what’s acceptable before your agents go live.
IGNA can help organizations define acceptable use, restricted use, data access expectations, review models, and first-agent readiness. A clear AI policy is not a barrier to AI adoption - it is the foundation that makes safe adoption possible.
01
Acceptable use definition
What AI agents are permitted to do, with which data, and for which users.
02
Restricted use boundaries
What agents must not do, which data they cannot access, and what always requires human review.
03
Data access expectations
Which data sources are approved, who can access them, and how access is audited over time.
04
First-agent readiness
A structured assessment of process maturity, data readiness, and governance prerequisites before pilot.
Process-first adoption
IGNA starts with the workflow, the process maturity, the risks, and the expected outcome - not with the model. Every deployment is grounded in operational reality.
Governed AI agents
Approved data, role-based access, human review, audit trails, and escalation rules are core to the IGNA operating model - not add-ons applied after the fact.
Enterprise integration
Connect to documents, systems, APIs, knowledge bases, workflows, and legacy applications - where appropriate and with the right governance controls in place.
Define your AI governance before you scale
Start with an AI policy + agent readiness assessment in the 30-Day Sprint.
Process-first adoption
IGNA starts with the workflow, the process maturity, the risks, and the expected outcome - not with the model. Every deployment is grounded in operational reality.
Governed AI agents
Approved data, role-based access, human review, audit trails, and escalation rules are core to the IGNA operating model - not add-ons applied after the fact.
Enterprise integration
Connect to documents, systems, APIs, knowledge bases, workflows, and legacy applications - where appropriate and with the right governance controls in place.