Business Solution · AI agent & automation governance

Govern AI agents in the same model as your systems.

Define agents, foundation models, autonomy tiers, and human-in-the-loop requirements in the architecture DSL. Scapius shows which systems and data each agent can reach and where human escalation applies.

Why this is hard today

Enterprises are adopting generative AI and autonomous agents rapidly, creating shadow-AI risks where models interact with sensitive data and systems without documented boundaries or audit trails.

System and AI Agent Integration Landscape showing conversational copilots and autonomous fraud investigators.

Integration landscape view showing AI agent integrations, foundation models, telemetry pipelines, and human escalation paths.Enlarge

Why AI agent governance brings clarity

Agent registry

Maintain a clear inventory of autonomous agents, foundation models, and execution scopes.

Human oversight

Declare and enforce mandatory human review gates for high-stakes actions directly in code.

Data boundaries

Prevent autonomous agents from accessing restricted ledger stores without explicit authorization.

Decisions enabled

Decisions informed by this model

Direct model queries replace subjective opinions with objective architecture evidence for leadership discussions.

Enterprise agent registry

Provides risk committees with a complete registry of enterprise AI agents, underlying models, and autonomy tiers.

Enforced review gates

Verifies that high-stakes autonomous workflows declare explicit human review gates in the architecture model.

Continuous permission audit

Enables continuous auditing of AI tool permissions and data access boundaries across departments.

Key review question

“Which AI agents operate autonomously, and are required human-in-the-loop guardrails enforced for critical decisions?”

How your architects maintain it

Defined as clear, structured text

Scapius provides native agent constructs in the architecture DSL. Teams define foundation models, autonomy tiers, and human-in-the-loop requirements alongside traditional applications to maintain clear AI oversight.

application/ai_agents.ea

DSL

agent agent_fraud_detective "AI Fraud Investigation Detective" {
    description "Autonomous agent analyzing transaction patterns and drafting SAR dossiers"
    model "gpt-4o"
    ai_governance {
        autonomy_level "Autonomous"
        human_in_loop true
    }
    relationships {
        this reads data_ledger_tx "Consumes real-time transaction event stream"
        this serves compliance_officer "Drafts suspicious activity dossiers for human signoff"
    }
}