Agentic AI

Governed Agentic AI for enterprise systems.

AI agents should not live outside enterprise systems. They must operate inside governed workflows, with permissions, traceability and human control.

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Inside the platform

Governed AI agents, managed like any enterprise asset.

Works Platform AI Agents console: agents, models, permissions, audit and runtime

Agents, models, permissions, audit and runtime, configured and supervised inside Works Platform.

The enterprise AI problem

Generic AI is hard to trust where it matters most.

Generic AI is difficult to control

Weak auditability

Risk on sensitive data

No process integration

No clear execution boundaries

The Caciopee approach

Agents that live inside your governed processes.

AI agents embedded inside Works Platform

Connected to workflows, screens, documents and rules

Operating under ACL / RBAC permissions

Every action traceable

Configurable human validation

Multi-LLM orchestration

LLM-provider independent

Deployable in controlled or sovereign environments

Types of agents

Specialized agents for real enterprise work.

Document Analysis Agent

Data Validation Agent

Compliance Scoring Agent

Workflow Assistant Agent

Business Rule Assistant

User Support Agent

Legacy Knowledge Extraction Agent

Specification Generation Agent

Risk Detection Agent

Decision Support Agent

Agentic AI use cases

From documents to decisions.

Validate documentsExtract informationDetect inconsistenciesSuggest next actionsScore complianceSupport users in forms and workflowsGenerate specificationsAnalyze legacy codeHelp configure applications

Governance

Control is not an afterthought.

Access control

Execution boundaries

Human-in-the-loop

Audit trail

Prompt and response logging

Data minimization

Model independence

Controlled deployment

Have an AI use case in a regulated process?

Let's discuss how governed agents fit inside your workflows.

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