AI Agent for Market Research — Built for GitHub
Automate Market Research for teams using GitHub. Arahi AI agents handle the workflow end-to-end — no code, set up in minutes.
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.
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 GitHub
Authorize GitHub and Arahi AI hooks into your issues, repos, and deployment pipelines.
Configure Dev Workflows
Define triggers for GitHub events — new issues, PR merges, build failures — and the AI actions to take.
Ship Faster with Less Toil
AI automates the tedious parts of your GitHub workflow. Track issues triaged, alerts handled, and developer time saved.
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
Yes. You define exactly which GitHub events start market research workflows — new records, status changes, messages, or custom triggers. Each trigger can have conditions so market research actions only fire when your specific criteria are met in GitHub.
Yes. The market research agent connected to GitHub simultaneously interacts with 1,500+ other apps — CRMs, databases, email platforms, and more. A single market research workflow can pull data from GitHub, process it, and push results to multiple destinations.
The GitHub integration automates end-to-end market research — including data capture from GitHub, validation, routing, follow-up actions, and status updates. Every market research step that touches GitHub can be handled by the AI agent.
Yes. You can create parallel market research workflows that respond to different GitHub events or conditions. For example, one market research flow for new GitHub records and another for updated ones — each with independent rules and actions.
No coding required. The no-code builder walks you through connecting GitHub and configuring market research rules visually. Your team can set up, modify, and manage GitHub-based market research workflows without any developer involvement.
All data exchanged between GitHub and Arahi AI during market research processing is encrypted in transit and at rest. We use OAuth tokens for GitHub access, never store raw credentials, and maintain full audit logs of every market research action.
The GitHub integration maintains a persistent real-time connection for market research automation with automatic retry logic and continuous monitoring. If GitHub experiences downtime, queued market research tasks process automatically once connectivity resumes.
Manual market research in GitHub requires constant tab-switching, copy-pasting, and follow-up tracking. Arahi AI eliminates this by handling market research tasks in real-time as GitHub events occur — running 24/7 with consistent accuracy and zero fatigue.
Arahi AI connects to GitHub via one-click OAuth, then runs market research workflows that read and write GitHub data on a schedule or in response to triggers. You configure the rules once; the agent executes market research across every relevant GitHub record without developer involvement.
GitHub holds the data; AI supplies the judgment and throughput. Together they turn market research from a manual, inconsistent process into one that runs at machine speed with a consistent quality bar — freeing your team to focus on the GitHub-adjacent work that genuinely needs human attention.
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