A weekly competitive brief, not a 4-hour read of changelog feeds.
ChatGPT watches your competitors' blogs, changelogs, pricing pages, hiring posts, and ad spend, and synthesizes a one-page brief with the changes that actually warrant your attention.
Brief drafted — 12 sources cited. Action items pulled:
Meeting notes
- • Lindy launched a $99 starter tier — undercutting our Pro by $50.
- • Relay shipped a Slack-native agent builder; demo gif on landing page.
- • Stack AI raised $25M; expect aggressive ad spend through Q2.
How does OpenAI (ChatGPT) work for market research automation?
OpenAI (ChatGPT) works for market research automation by powering an Arahi AI agent that runs the workflow end-to-end inside your existing tools — no code, no custom build. The agent connects to OpenAI (ChatGPT) alongside the other apps your team already uses, watches for the triggers that matter for market research, and takes the next step on its own while keeping a complete audit trail for review. AI gathers market data from hundreds of sources and synthesizes it into actionable reports. Teams typically see days → Hours from scoping to report once the agent is in production. You stay in control: every action is logged, confidence thresholds are configurable, and anything ambiguous is queued for a human instead of being silently auto-completed.
Built in plain English.
You write the rule the way you'd describe it to a teammate. The agent reads the rule, breaks it into the actions it'll take, and confirms the apps it'll touch — before it does anything.
- 1Read the meeting transcript end-to-end
- 2Extract decisions, commitments, and next steps
- 3Update the deal record and advance the stage if criteria met
- 4Notify the right teammate with the relevant context
Get started in three steps
Connect OpenAI (ChatGPT)
Authorize OpenAI (ChatGPT) in your Arahi AI dashboard. The secure connection takes less than 60 seconds.
Configure Your AI Agent
Set up triggers, actions, and conditions specific to how your team uses OpenAI (ChatGPT).
Deploy & Monitor Results
Your AI agent goes live immediately. Track tasks automated, time saved, and accuracy metrics in real-time.
Lindy launched a $99 starter tier — undercutting our Pro by $50.
Action items extracted; assignees notified in Slack.
Three deals moved to next stage; risks flagged for the AE.
Approve before it sends.
Every draft lands in a review queue. You approve, edit, or reject — the agent never acts on its own unless you explicitly turn that on for a workflow you trust.
Every action, with the reasoning attached.
Each step the agent takes is logged with what it did, why it did it, and which app it touched. Audit-ready, so security and compliance can sign off without backfilling.
- Agent2:47 PM
Updated Notion · Compete tracker with the meeting outcome.
- Agent2:46 PM
Advanced deal stage; the criteria for Proposal were met.
Reason: Budget confirmed and decision-maker identified per stage definition.
- Agent2:45 PM
Wrote meeting notes for Competitor brief · Week of Mar 10.
- Agent2:44 PM
Read the transcript and extracted action items.
- Agent2:30 PM
Triggered by call end event in Granola.
Frequently asked questions
Competitor blogs, changelogs, pricing pages, careers pages, GitHub repos (if public), G2 reviews, ad libraries (LinkedIn, Meta), and news mentions. You can add custom sources — Slack channels, podcasts, newsletters.
It learns from what your team actually clicks and acts on. If you ignore pricing changes but care about feature shifts, the brief tilts that way over time.
It can read public signals that imply private ones (e.g., a competitor hiring 8 EU compliance roles suggests an EU push). It doesn't scrape gated content or violate ToS on closed networks.
Yes. Each flagged item comes with a suggested action — a counter-positioning post, a sales talk-track update, a product roadmap input — for your team to accept or discard.
A Notion or Google Doc page each Monday, plus a Slack thread in #compete. Annual archive maintained for trend lookups.
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