AI AGENTS
Quote Reply Parser to Coda Tracker
Watches a procurement inbox for incoming supplier quote emails, extracts price and terms from each one, and appends them as a structured row in a Coda quote tracker.
How it runs
The automated pipeline, trigger to output.
- TriggerSupplier quote email received in GmailGmail
- LogicFilter to known suppliers, drop non-quotes
- ActionExtract price and terms with OpenAIOpenAI
- LogicMatch quote to existing RFQ and supplier
- OutputAppend parsed quote row to Coda trackerCoda
What it does
Catches supplier quote emails the moment they arrive and turns the unstructured message (and any attached PDF or body text) into a tidy Coda row. No more copy-pasting prices out of email threads.
When to use it
Use it when suppliers reply to your RFQs on their own schedule and you want every quote logged and comparable without a buyer manually transcribing each email.
How it works
- 1An incoming email matching your quote label or address in Gmail fires the trigger.
- 2Logic checks the sender against your known-supplier list and discards anything that isn't a quote.
- 3OpenAI reads the email body and extracts unit price, currency, lead time, validity date, and payment terms into structured fields.
- 4Logic maps the supplier to its existing tracker entry, or creates a new supplier reference if it's a first-time bidder.
- 5The parsed quote is appended as a new row in the Coda tracker, timestamped and linked to the originating RFQ.
Set it up
What you configure once, before turning it on.
- 1Connect GmailRead, draft, send, label.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect CodaDocs, packs, automations.
- 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.
