No-code automation built into the data graph.
Triggers from any module, conditions over the whole graph, actions across every module. The same engine your AI agents call — because what AI can automate, you can also script and audit.
What Automation does for you
Triggers anywhere
Sales stage changes, ticket events, project milestones, AI agent decisions, scheduled times — anything that produces a graph event.
Conditions across modules
Filters that read across module boundaries. "If deal closed and customer has no open ticket and project budget is under threshold, then..."
Actions on every record
Create, update, route, message, invoice, schedule. Same actions an agent calls — so what humans script, AI can call too.
Auditable, testable
Every run is logged. Test mode replays a trigger without taking action. SOC 2 controls apply to automation runs.
The engine your humans script and your agents call.
Cyril doesn’t have a separate "AI workflow" and "no-code workflow" — they’re the same engine. What an agent can do via natural language, your operator can also script in the visual builder. One audit log, one test surface.
- AI agents call into the same actions as no-code automations
- Test mode replays a real trigger without producing side effects
- Versioning: every automation has a history with rollback
Common Automation questions
They work together. Use AI agents for one-off and judgement-heavy work; use automations for high-volume, deterministic flows. Both call the same actions — and you can promote a working agent flow into an automation when it’s proven.
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