Solutions / Platform / SRE team
Platform / SRE team
Build the AI OS on top of your existing platform.
Argy lets platform teams expose AI and DevSecOps capabilities without replacing the existing toolchain.
Outcomes
- • Single LLM entry point
- • Industrialized workflows
- • Run automation
Typical automations
KPIs to track
- • MTTR
- • AI request success rate
- • Onboarding time
Priorities
- • Standardize without becoming a ticket factory
- • Provide an abstraction between teams and models
- • Make run outcomes measurable and automatable
Argy approach
- • Versioned modules published in a self-service catalog
- • Gates, approvals, and policies embedded
- • Observability and runbooks as standards
Key building blocks
- • Module Studio + catalog
- • Orchestrator and agents for execution
- • LLM Gateway and audit logs
Governance & sovereignty
- • RBAC/SSO and role separation
- • Adoption tracking and exception control
- • LLM routing and quotas per team
Direct answers
Does Argy replace our tools?
No. Argy orchestrates your toolchain and adds the governed AI layer between teams and models.
How do we avoid forks and fragmentation?
By publishing versioned golden paths and centralizing model access through the LLM Gateway.
Related use cases
Explore concrete scenarios aligned with this solution.
Launching an IDP for a scale-up
Argy helps launch an IDP quickly: modules, portal, and governance are ready on your toolchain.
Standardizing multi-team delivery
Argy brings shared standardization without blocking team autonomy.
Accelerating environment provisioning
Argy packages infrastructure and standards into reusable modules that teams can instantiate on demand.
Steering execution (SLOs, observability, FinOps)
Argy standardizes run practices: observability, routines, and improvement loops are packaged and tracked.
Next step: request a demo or view pricing.