AI AGENTS
Fleet warranty renewal agent: gather quotes, recommend, await approval
An agent that for each expiring fleet warranty researches current renewal pricing, compares it against the asset's residual value, drafts a renew-or-retire recommendation.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule
- ActionPull 45-day expiries from PostgresPostgres
- ActionResearch renewal and replacement pricingPerplexity
- LogicCompare cost vs residual value, draft recommendation
- ActionSend owner a Teams approval cardMicrosoft Teams
- OutputWrite approved decision back to PostgresPostgres
What it does
Handles the judgment-heavy part of warranty renewals. For every asset nearing expiry, the agent looks up market renewal pricing, weighs it against residual value and repair history, writes a plain-English recommendation, and presents the owner an approve-or-override decision in Microsoft Teams.
When to use it
Use it for fleets or capital equipment where renew-versus-retire is a real financial call, not a rubber stamp, and you want a reasoned recommendation prepared before a human signs off.
How it works
- 1A daily schedule starts the agent run.
- 2The agent pulls assets expiring within 45 days from the Postgres asset table.
- 3For each asset it searches the web for current renewal and replacement pricing via Perplexity.
- 4A reasoning step compares renewal cost to residual value and repair frequency and drafts a recommendation with rationale.
- 5The agent sends the owner a Teams approval card showing its recommendation and the supporting numbers.
- 6On approval, it writes the decision and effective date back to Postgres.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect PerplexitySearch-grounded answers with citations.
- 3Connect Microsoft TeamsChannels, chats, files.
- 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
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.
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.
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.
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.
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.
Weekly On-Call Doc-Gap Digest
Each week the agent reviews every Sentry issue resolved in the last 7 days, ranks the ones whose runbook coverage is missing or thin.
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.