Intelligence
Model-backed workers with clear boundaries and controls
How agents are scoped, which tools they may use, and how prompts and outputs are recorded for audit. Placeholder for the full product-security narrative.
CTOs, ML leads, and information security teams assessing AI usage in enterprise workflows.
Placeholder technical detail
The sections below are structural placeholders. Replace with deep dives, diagrams, and links to your architecture and security materials as they are finalised.
Governance in scope
Tooling limits, PII handling, and escalation rules. This page will link to your data-processing agreements and model policies.
Observability
Traceability from a workflow step to the underlying model call. Cross-reference with the Observability cap capability.
At a glance
- No silent autonomy: every action is policy-bound
- Suitable for regulated and document-heavy work
- Stays on your stack when you self-host
Other platform areas
Explore the rest of the platform from a technical perspective.
Your infrastructure. Your data.
Automate smarter. Stay in control.
Deploy Lunnoa inside your own infrastructure. Every workflow, every agent run, and every data point stays in your environment, with full governance from day one.
Self-hosted · Deployed within days · Flat licence, unlimited usage · Full IT governance
Your Infrastructure
Governance layer
Govern
Build
WorkflowsAgentsKnowledge basesSkillsToolsAutomate
RoutingWorkflow EngineSchedulingAgent JobsObserve
LogsTracesJob HistoryConversationsExecutions
