AI AGENTS
On-Demand Competitor Pricing Lookup (Chat)
A chat-triggered agent that, when a rep asks about a competitor in Slack, scrapes that competitor's live pricing on the spot, summarizes it against your own plans.
How it runs
The automated pipeline, trigger to output.
- TriggerChat message naming a competitor
- LogicResolve name to known pricing URL
- ActionScrape competitor pricing live (Firecrawl)Firecrawl
- ActionBuild side-by-side comparison (OpenAI)OpenAI
- OutputReply in Slack thread with talking pointSlack
What it does
This is a conversational agent your sales reps invoke mid-deal. Ask it about a competitor by name and it fetches that competitor's current pricing live, compares it to your equivalent plans pulled from your own pricing table, and answers in the thread with a concise, deal-ready comparison.
When to use it
Use it when reps need an answer in seconds during a live conversation and the weekly digest is too stale or too broad. It answers the specific 'how do we compare to X right now' question without anyone leaving Slack.
How it works
The agent is triggered by a chat message naming a competitor. A logic step resolves the name to a known pricing URL from your Postgres watchlist (or asks for clarification if unknown). Firecrawl scrapes that page live, and an OpenAI step builds a side-by-side comparison against your own plans, highlighting where you win on price or value. The agent replies directly in the Slack thread with the comparison and a one-line recommended talking point the rep can use immediately.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect FirecrawlCrawl, scrape, structured extract.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More AI Agents workflows
Observability Cost Allocation Report
Monthly, an agent pulls Datadog and Honeycomb usage, allocates spend to teams and services by tags, writes the breakdown to Snowflake, and posts a chargeback summary to Slack.
Vendor Shortlist Matrix from a Buying Brief
An agent reads a buying brief, researches candidate vendors across the live web, and builds a scored comparison matrix in Coda ranking each vendor against your stated criteria.
Split oversized Linear epics into estimated child issues
An agent scans newly created Linear epics, breaks each one above a size threshold into discrete child issues with point estimates and acceptance criteria.
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.
Buying Brief Email to Shortlist Doc in Drive
When a buying brief arrives by email, an agent researches the market and produces a polished narrative shortlist document in Google Drive, then replies to the sender with the link.
Zoom Demo Low-Score Objection Escalation to Manager
Scores how well a rep handled objections in each Zoom demo, and only when the handling score falls below a threshold does it create a coaching task in ClickUp and alert the rep's…
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.