Who Orlo Is For
Orlo serves multiple audiences, but not every surface is equally useful to every audience.
The common thread is simple: Orlo is most useful when AI is on a consequential production path and the organization needs to prove, govern, observe, and improve the system.
Open Core is best for
Platform and ML engineers
Use Open Core if you want:
- reusable validation primitives
- runtime adapters
- SDKs for agent-step governance
- embeddable Web Components
Technical evaluators
Use Open Core if you are trying to understand:
- how Orlo approaches validation
- how Orlo models agent-step governance
- how Orlo packages its UI and adapter layers
Orlo Platform is best for
Infrastructure and platform leaders
Use Orlo Platform if you need:
- one governed system for multiple teams
- org-scoped controls and audit trails
- deployment and inference governance
- a clear integration API with operational behavior
Domain team leads
Use Orlo Platform if you want to:
- upload task data
- compare models
- deploy a winner
- review feedback
- operate AI safely without building the stack yourself
This is especially relevant when a bad answer, stale retrieval result, unreviewed write action, or weak approval path can create a real business consequence.
Risk, compliance, security, and internal audit
Use Orlo Platform if you need to see:
- which AI tasks exist and who owns them
- which models, prompts, datasets, retrieval settings, validation rules, and routing policies were approved
- how outputs were validated before use
- when human approval was required
- what evidence exists after a production decision
- whether incidents and feedback became future controls
Orlo does not replace legal sign-off, risk registers, or compliance management systems. It gives those functions the operational proof they need from the AI runtime.
Honest Boundary
Open Core is highly useful, but it is not the full self-serve product for a non-technical domain team.
That full experience lives in Orlo Platform.