Use cases / Building assistants and AI agents
Building assistants and AI agents
Argy provides the foundation to ship reliable agents: RAG context, controlled tools, and native governance.
Context
Each team experiments with agents without a shared framework or data boundaries.
Argy solution
Governed agents connected to RAG, orchestrated by reusable modules and policies.
Key challenges
- • Isolated agents without standards
- • Risk of sensitive data leakage
- • Hard to move from POC to production
Argy approach
- • Governed agents with pre-action checks
- • RAG scopes for controlled context
- • Modules to package workflows as capabilities
Building blocks
- • Argy Chat and Argy Code as references
- • LLM Gateway to secure calls
- • Module Studio to package workflows
Governance & sovereignty
- • Approvals and tool allowlists
- • Agent action audit trails
- • Multi-tenant isolation and access control
KPIs to track
- • Time-to-production
- • Agent success rate
- • Data incidents
Related automations
Example workflows you can assemble for this use case.
Governed HR assistant via MCP + Argy Chat
Steps
- • Action 1: create an MCP server connected to the internal HR tool via Argy Code
- • Action 2: run a deployment and validation pipeline
- • Action 3: publish the tool in Argy Chat for employees
Outcomes
- • Self-service HR access
- • Protected data
Finance and procurement assistant
Steps
- • Connect ERP/procurement via MCP
- • Define policies and approvals
- • Expose in Argy Chat with team scopes
Outcomes
- • Faster decisions
- • Approval traceability
Explore more in automatable actions.
Related solutions
How leaders frame this use case across teams.
Platform / SRE team
Build the AI OS on top of your existing platform.
CTO / VP Engineering
Scale enterprise AI without losing control.
Security / GRC
Govern AI and DevSecOps with evidence and sovereignty.
Next step: request a demo or explore solutions.