AI Agent for Market Research — Built for GitLab
Automate Market Research for teams using GitLab. 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 GitLab
Authorize GitLab and Arahi AI hooks into your issues, repos, and deployment pipelines.
Configure Dev Workflows
Define triggers for GitLab 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 GitLab 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 GitLab 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 GitLab.
Arahi AI connects natively with GitLab to handle the full market research workflow. The AI agent monitors GitLab events, processes market research tasks automatically, and writes results back to GitLab — no copy-pasting or tab-switching required.
The GitLab integration automates end-to-end market research — including data capture from GitLab, validation, routing, follow-up actions, and status updates. Every market research step that touches GitLab can be handled by the AI agent.
The dashboard shows market research-specific metrics for your GitLab integration — tasks processed, average handling time, success rates, and escalation frequency. You can track how GitLab-triggered market research workflows perform over time.
No coding required. The no-code builder walks you through connecting GitLab and configuring market research rules visually. Your team can set up, modify, and manage GitLab-based market research workflows without any developer involvement.
Yes. You can run market research workflows in test mode using sample GitLab data before activating on live records. This lets you verify every market research rule works correctly with your GitLab setup before processing real data.
Yes. You can create parallel market research workflows that respond to different GitLab events or conditions. For example, one market research flow for new GitLab records and another for updated ones — each with independent rules and actions.
Manual market research in GitLab requires constant tab-switching, copy-pasting, and follow-up tracking. Arahi AI eliminates this by handling market research tasks in real-time as GitLab events occur — running 24/7 with consistent accuracy and zero fatigue.
Arahi AI connects to GitLab via one-click OAuth, then runs market research workflows that read and write GitLab data on a schedule or in response to triggers. You configure the rules once; the agent executes market research across every relevant GitLab record without developer involvement.
GitLab 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 GitLab-adjacent work that genuinely needs human attention.
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