AI AGENTS
Front Out-of-Band Discount Escalation Router
Detects when a prospect's ask exceeds your approved discount ceiling and routes a structured approval request to deal desk in Slack instead of drafting a reply.
How it runs
The automated pipeline, trigger to output.
- TriggerInbound reply on Front negotiation threadFront
- LogicExtract requested discount from message
- ActionFetch list price and approved ceilingPostgres
- LogicBranch: ask over the approved band?
- ActionLog over-band request for auditPostgres
- OutputPost approval request to deal-desk SlackSlack
What it does
This agent reads incoming Front negotiation replies, calculates the requested discount against the account's approved band in Postgres, and when the ask is over the line it does not draft a concession. Instead it assembles a one-click approval request for deal desk with the deal context and the exact overage.
When to use it
Use it when reps need a fast, auditable path for asks that exceed standing guardrails. It prevents rogue discounting by forcing anything out-of-band through a named approver, while keeping everything anchored to the original Front thread.
How it works
- 1An inbound Front message on a negotiation conversation triggers the run.
- 2The agent extracts the requested price or discount from the message.
- 3It pulls the account's list price and maximum approved discount from Postgres.
- 4A branch compares the ask to the ceiling: in-band asks are skipped, over-band asks continue.
- 5For over-band asks it logs the request and overage to Postgres for audit.
- 6It posts a structured approval card to the deal-desk Slack channel with approve/deny context and a link back to the Front thread.
Set it up
What you configure once, before turning it on.
- 1Connect FrontShared inbox, conversations.
- 2Connect PostgresAny Postgres URL — query, write, migrate.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More AI Agents workflows
Stale Doc-PR Chaser for Runbook Gaps
On a daily schedule the agent finds runbook doc PRs that were opened from resolved incidents but never reviewed, summarizes what each one fixes.
On-Call Runbook Gap Closer: Resolved Sentry Issues to Doc PRs
An agent reads each newly resolved Sentry issue, compares the actual fix against your existing runbook, and opens a GitHub PR adding the missing remediation steps.
Datadog Bill Spike Attribution Agent
When a daily Datadog cost check detects a spend jump, an agent attributes the increase to the specific services and metric types driving it and posts a ranked breakdown to Slack.
Sentry-to-Confluence Runbook Updater
When a Sentry issue is resolved, the agent finds the matching Confluence runbook page and proposes an inline update with the verified fix.
Custom Metrics Cardinality Spike Pager
A webhook from a Datadog monitor fires when custom-metric cardinality jumps; an agent pinpoints the offending metric and tag, estimates the added cost.
Resolved Incident to Public Troubleshooting Doc
For customer-facing errors resolved in Sentry, the agent drafts a sanitized troubleshooting entry and opens a PR to your ReadMe documentation.
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.
