Automation in Fibery: Rules, Not a Visual Flow Builder
Fibery's automation runs on its internal Rules engine: you pick a trigger (an entity is created, a field changes, a schedule fires), optional conditions, and one or more actions — update a field, create a linked entity, post a Slack message, or call a webhook. It executes only against Fibery's own entities and relations; it's not a general-purpose, drag-and-drop flow builder that connects arbitrary external apps the way Zapier or Make does.
Who this is for: teams who want to cut down on manual field updates and status changes inside Fibery itself, not teams looking to orchestrate a multi-app pipeline from a single canvas.
Delivery components
- Mapping of the manual, repetitive field updates and entity-creation steps worth turning into Rules (e.g., auto-set a due date when status changes to "In Progress").
- A built set of Rules covering the team's actual trigger/condition/action needs, tested against edge cases like bulk edits and imports.
- A clear split of what runs as a native Rule inside Fibery versus what needs the Zapier/Make connector or the API — cross-tool automation, like pushing a new entity into a CRM, is not a Rules capability.
- Webhook and API credential setup for the subset of automation that has to reach outside Fibery.
- A short runbook for debugging a broken Rule (checking trigger conditions and execution history) versus a broken external integration, since the failure modes look different.
Rules live inside the same Types and relations you've already modeled, so a Rule that updates a linked entity depends on that relation existing and being named consistently — restructuring your data model later means revisiting any Rule built against the old structure.
A small team usually needs only a handful of Rules covering status transitions and notifications. Larger teams running Fibery as their system of record tend to accumulate many small Rules over time, at which point auditing which ones are still relevant becomes its own maintenance task.
The result is fewer manual status updates and fewer things falling through the cracks inside Fibery itself — paired with an honest map of where Rules stop and where Zapier, Make, or the API have to pick up the rest.
Fibery introduces Automation by establishing a reusable rules engine tailored to your data model.
- Automatic triage of incoming requests based on field values and ownership
- Dynamic task routing that adapts to workload and availability
- Automated status updates and notification campaigns triggered by milestone changes
- Data-derivation pipelines that transform inputs into standardized records
- Quality checks that run on record creation with immediate remediation paths
- Auditable decision logs for compliance and governance
- Escalation workflows that trigger corrective actions when thresholds are crossed
- Retry and back-off strategies that handle transient failures
- Cross-project syncing to ensure consistency across Fibery workspaces
- Self-service automation templates for product teams
These use cases illustrate how Fibery underpins automation with tangible outcomes, while keeping the implementation approachable for teams new to the platform.