HeyMarvin and Koji are both AI meeting assistants for recording, transcription, and summaries, compared here on pricing, features, and workflow fit. HeyMarvin: AI research assistant that records and transcribes user-research interviews and builds a searchable insights repository. Koji: AI-native customer research platform whose AI interviewer runs voice and text discovery conversations at scale, then synthesizes themes automatically. They overlap on ai-meeting-assistants, so the right pick depends on team size, budget, and which meeting workflows you automate.
For ai-meeting-assistants workflows, shortlist HeyMarvin when ux researchers transcribing and tagging user-interview calls matters most, and Koji when running exploratory discovery interviews without scheduling live calls matters most. Both record across Zoom, Google Meet, and Microsoft Teams; trial each on real meetings before committing.
AI research assistant that records and transcribes user-research interviews and builds a searchable insights repository.
AI thematic analysis that clusters feedback into themes and patternsAsk AI querying across research data with citations to source clipsRecords and automatically transcribes user-research interview calls
AI-native customer research platform whose AI interviewer runs voice and text discovery conversations at scale, then synthesizes themes automatically.
AI interviewer that runs asynchronous voice and text discovery conversations at scaleAI research agent that drafts research goals and interview guides from a briefAutomatic per-interview analysis with key moments and sentiment
HeyMarvin is a free tier with paid upgrades (freemium); Koji is a free tier with paid upgrades (freemium). Always confirm current pricing on each vendor's site before buying.
Records and automatically transcribes user-research interview calls
AI interviewer that runs asynchronous voice and text discovery conversations at scale
Standout feature
Time-stamped notes and collaborative live note-taking during sessions
AI research agent that drafts research goals and interview guides from a brief
Team usage
AI thematic analysis that clusters feedback into themes and patterns
Automatic per-interview analysis with key moments and sentiment
Integrations
Ask AI querying across research data with citations to source clips
Cross-interview synthesis into study-wide themes, patterns, and recommendations
Languages & capture
Searchable centralized research repository combining many data sources
Insights traceable back to specific participant quotes
Best-fit workflow
Video clips, highlight reels, and insight reports for sharing findings
MCP integrations with Claude, ChatGPT, Cursor, and Notion
Best for
HeyMarvin
Choose HeyMarvin if you need ux researchers transcribing and tagging user-interview calls — strengths include tailored to user-research interviews rather than generic meeting notes.
Koji
Choose Koji if you need running exploratory discovery interviews without scheduling live calls — strengths include removes scheduling overhead by running many interviews in parallel and asynchronously.
Pros & cons
HeyMarvin
+ Tailored to user-research interviews rather than generic meeting notes
+ Combines capture, AI analysis, and a repository in one workflow
- Oriented to research teams, so less relevant for everyday internal meetings
Koji
+ Removes scheduling overhead by running many interviews in parallel and asynchronously
- AI-moderated async format is less suited to deep rapport-driven live interviews
FAQ
Is HeyMarvin or Koji better for AI meeting notes?
It depends on your workflow. HeyMarvin is strong for ux researchers transcribing and tagging user-interview calls, while Koji is strong for running exploratory discovery interviews without scheduling live calls. Both transcribe and summarize meetings.
How do HeyMarvin and Koji compare on price?
HeyMarvin is a free tier with paid upgrades and Koji is a free tier with paid upgrades. Check each vendor's pricing page for the latest plans and free-tier limits.
Can I use both HeyMarvin and Koji?
Yes. Many teams run more than one meeting assistant when the workflows are complementary and the budget is justified.