CUSTOMER SUPPORT
Hourly Front workload rebalance with Postgres-tracked agent capacity
On a schedule, compares each agent's open Front conversation count against their configured capacity in Postgres and redistributes the overflow from overloaded agents to those…
How it runs
The automated pipeline, trigger to output.
- TriggerHourly schedule during business hours
- ActionSnapshot open-conversation count per agentFront
- ActionLoad per-agent capacity and skills from PostgresPostgres
- LogicCompute overflow and target agents with headroom
- ActionReassign overflow conversations in FrontFront
- OutputWrite rebalance log row to PostgresPostgres
What it does
Every hour this workflow takes a snapshot of how many open conversations each Front teammate holds, compares it against per-agent capacity limits stored in Postgres, and moves the oldest excess conversations off anyone over their cap onto teammates who still have room. The result is a self-leveling inbox that respects each person's real capacity.
When to use it
Use it for teams where agents have different capacities (part-time, tier-2, leads) and you want steady proactive rebalancing instead of reacting only when SLAs are at risk.
How it works
- 1A scheduled trigger runs the rebalance every hour during business hours.
- 2The flow loads the live open-conversation count per agent from Front.
- 3It reads each agent's configured capacity and skill tags from a Postgres table.
- 4A balancing step computes who is over capacity and which conversations (oldest first) should move to agents with headroom.
- 5Front reassigns each selected conversation.
- 6The run writes a rebalance log row to Postgres for reporting and auditing.
Set it up
What you configure once, before turning it on.
- 1Connect FrontShared inbox, conversations.
- 2Connect PostgresAny Postgres URL — query, write, migrate.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More Customer Support workflows
Close the loop with requesters when a Linear bug moves to Done
When a Linear issue created from a support escalation moves to Done after deploy, look up the originating Zendesk tickets and notify each requester that their reported bug is…
Reopen and notify Front conversations when their bug fix deploys
When a deploy resolves a Sentry issue, find the snoozed or closed Front conversations linked to it, reopen them, and send the customer a reply that the fix is now live.
Suggest the right Loom video by classifying Intercom message intent
Reads each new inbound Intercom conversation, classifies what the customer is trying to do, and surfaces the best-matching Loom walkthrough to the agent as an internal note.
Draft personalized fix-live replies for support to review
When a Sentry issue resolves, an agent reads each linked ticket's full thread and drafts a tailored 'your fix is live' reply per requester.
Send a tailored Loom onboarding sequence on Front first-reply
When a new customer's first email lands in Front, this picks the Loom onboarding walkthroughs matching their plan and use case, builds a friendly sequenced reply.
Article Volume-Rebound Early Warning (Datadog)
Streams support ticket-tag events into Datadog, watches for topics whose volume is reaccelerating against a decaying article.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.