{"site":{"name":"Koji","description":"AI-native customer research platform that helps teams conduct, analyze, and synthesize customer interviews at scale.","url":"https://www.koji.so","contentTypes":["blog","documentation"],"lastUpdated":"2026-05-29T22:34:31.863Z"},"content":[{"type":"documentation","id":"e83f7cab-671a-4770-890e-a994f6572fd1","slug":"koji-vs-granola","title":"Koji vs Granola: AI Interviewer vs AI Notetaker for Customer Research (2026)","url":"https://www.koji.so/docs/koji-vs-granola","summary":"Granola is an AI notetaker that captures meetings you attend; Koji is an AI interviewer that conducts and analyzes interviews at scale. Choose Granola to improve notes on calls you join; choose Koji to run more interviews than you can personally attend. Many teams use both.","content":"**Short answer:** Granola and Koji solve different halves of the research problem. Granola is an AI *notetaker* — it sits on a call you are already attending, transcribes it, and turns your shorthand into polished notes. Koji is an AI *interviewer* — it conducts the conversation for you, moderating live voice or text interviews with dozens or hundreds of customers in parallel, then aggregating every transcript into a themed report automatically. If your bottleneck is remembering what was said in calls you join, choose Granola. If your bottleneck is the *number of interviews one researcher can run*, choose Koji. The two are complementary, and many research teams run both.\n\n## The one-sentence distinction\n\nA notetaker captures a conversation a human is having. An interviewer *is* the conversation. That single difference explains almost every other difference below — pricing, scale, analysis, and the kind of insight you walk away with.\n\n## Quick comparison\n\n| | Granola | Koji |\n|---|---|---|\n| Category | AI meeting notetaker | AI interviewer + analysis platform |\n| Who talks to the customer | You (a human moderator) | Koji's AI moderator |\n| Interviews per researcher | One meeting at a time | Hundreds, running in parallel |\n| Best for | Notes from calls you already attend | Running *and* analyzing interviews at scale |\n| Structured questions | No | Yes — 6 question types |\n| Cross-interview analysis | Per-meeting summary | Automatic thematic aggregation across all sessions |\n| Participant recruitment | No (you bring the meeting) | Yes — share a link, collect responses 24/7 |\n| Voice & async | Live meetings you join | Async voice or text, on the participant's schedule |\n| Ideal user | Anyone in back-to-back calls | Researchers, PMs, and founders scaling discovery |\n\n## What Granola is — and what it is great at\n\nGranola is one of the most talked-about AI productivity tools of 2026. In March 2026 it raised a **$125 million Series C led by Index Ventures, reaching a $1.5 billion valuation** ([Bloomberg](https://www.bloomberg.com/news/articles/2026-03-25/ai-notetaker-granola-hits-1-5-billion-value-in-125-million-funding); [TechCrunch](https://techcrunch.com/2026/03/25/granola-raises-125m-hits-1-5b-valuation-as-it-expands-from-meeting-notetaker-to-enterprise-ai-app/)), on the back of roughly **250% revenue growth** in the prior quarter and enterprise adoption at companies like Vanta, Gusto, Asana, and Cursor.\n\nIts design is genuinely clever. Rather than dumping a raw AI summary on you, Granola keeps you an *active participant*: you jot down the moments that matter during the call, and after the meeting its AI enriches those notes with detail pulled from the full transcript. The result is notes that reflect what *you* thought was important, not a generic recap.\n\nFor research, Granola shines when:\n\n- You are personally on every customer call (sales discovery, support escalations, advisory-board sessions).\n- You want clean, shareable notes without typing during the conversation.\n- You need to query past meetings (\"what did enterprise customers say about pricing?\") across your own history.\n\nGranola is an excellent **memory and synthesis layer for meetings you attend**. What it does not do is hold the conversation for you, recruit participants, or run a study you are not personally sitting in.\n\n## What Koji is\n\nKoji is an **AI-native research platform** built around an AI interviewer. You define a research brief and questions; Koji generates a customizable AI consultant that conducts the interview — by voice or text — with each participant individually. Participants join from a shared link on their own schedule, and Koji adapts in real time: it asks intelligent follow-ups, probes vague answers, and keeps the conversation on-objective.\n\nCrucially, Koji does not just transcribe. It performs **automatic thematic analysis** across every interview, scores response quality on a 1–5 scale, and assembles a real-time report with themes, supporting quotes, and recommendations. The researcher moves from *running interviews* to *reading findings*.\n\nThis is the structural advantage. Qualitative research only produces reliable conclusions once you reach **saturation** — the point at which new interviews stop surfacing new themes. A widely cited review of empirical studies found that most behavioral and social research needs **between 9 and 17 interviews** to reach saturation, with the higher end required when your audience is diverse ([NN/g](https://www.nngroup.com/articles/interview-sample-size/)). As usability pioneer Jakob Nielsen put it, the smart move is to \"interview five users, find the issues, fix them, and then interview five more.\" A notetaker requires you to personally sit through all of those. An AI interviewer runs them in parallel while you sleep.\n\n## The core difference: capture vs. conduct\n\nPicture two bottlenecks.\n\n**Bottleneck A — \"I forget what people said.\"** You are already talking to customers, but notes are messy and details slip. Granola solves this perfectly. It is a capture tool.\n\n**Bottleneck B — \"I can't talk to enough customers.\"** You can only personally run so many calls a week, so your sample stays tiny and your conclusions stay shaky. No notetaker fixes this, because a notetaker still needs a human in every conversation. Koji solves it by *being* the interviewer — turning a 20-person study from three weeks of scheduling into a link you send once.\n\nMost teams have both bottlenecks. That is why the tools coexist rather than compete head-on.\n\n## Structured questions: a Koji differentiator\n\nBecause Koji runs the interview, it can blend open conversation with **structured questions** — six types that produce quantifiable data alongside narrative: `open_ended`, `scale`, `single_choice`, `multiple_choice`, `ranking`, and `yes_no`. That means a single Koji study yields both a clean chart (\"68% ranked price as their top concern\") *and* the verbatim \"why\" behind it, aggregated automatically. A notetaker, by definition, can only capture whatever was said in an unstructured meeting — there is no question framework to standardize answers across sessions. See the [structured questions guide](/docs/structured-questions-guide) for how to combine question types in one study.\n\n## When to choose which\n\n**Choose Granola if:**\n- You are on every customer call already and just want better notes.\n- Your research is opportunistic (insights surface in sales/support calls).\n- You want a personal, queryable memory of your own meetings.\n\n**Choose Koji if:**\n- You need to run more interviews than you can personally attend.\n- You want consistent questions and automatic cross-interview themes.\n- You want to recruit participants via a link and collect responses 24/7.\n- You need structured data and narrative from the same study.\n\n**Use both if:** you take live calls (Granola) *and* run scaled, repeatable studies between them (Koji). Granola makes you better in the room; Koji lets you be in a hundred rooms at once.\n\n## The modern approach with AI\n\nThe old research stack forced a trade-off: deep qualitative insight (slow, manual, small sample) *or* scale (surveys that strip out the \"why\"). AI-native tooling collapses that trade-off. Koji delivers the depth of a moderated interview at the scale of a survey, with analysis that used to take an analyst days finished in minutes. Granola, meanwhile, removes the friction of note-taking in the calls you do attend. Used together, they cover the full surface area of customer conversations — the ones you join, and the ones Koji runs for you.\n\n## A concrete scenario\n\nSay you are validating a new pricing tier. With Granola, you would schedule and personally run, say, eight customer calls over two weeks — Granola gives you clean notes from each, but you are still the constraint: eight calls is eight hours, and your eighth interview happens long after your first. With Koji, you write the brief once, share a link, and 40 customers complete a 10-minute voice interview on their own time over a weekend. Koji probes each one (\"you said the price feels high — compared to what?\"), then hands you a themed report: the recurring objections, the segment that loves the tier, and the verbatim quotes behind each. Same goal, radically different throughput.\n\n## Pricing and access models\n\nThe tools price for different jobs. Granola is a per-seat productivity subscription — you pay for the people taking notes. Koji prices around research volume (it offers a free tier with credits to start), because the unit of value is an *interview conducted and analyzed*, not a seat in a meeting. If ten people on your team take notes, Granola scales by seats; if you need to run a 100-person study, Koji scales by interviews. Neither model is \"cheaper\" in the abstract — they meter fundamentally different things.\n\n## Data, consent, and analysis depth\n\nBoth tools record and transcribe, so both require clear participant consent. The deeper difference is what happens *after* transcription. Granola enriches and stores notes for the meeting owner to revisit and query. Koji treats transcripts as a dataset: it scores response quality on a 1–5 scale, clusters themes across every session, and surfaces how much evidence sits behind each finding. For a single call, a notetaker's summary is plenty. For a study where you must defend a conclusion to stakeholders — \"how many people actually said this?\" — the aggregation layer is the entire point.\n\n## Related Resources\n\n- [How AI Interviewers Work](/docs/how-ai-interviewers-work)\n- [Koji vs Fathom: AI Notetaker vs AI Interviewer](/docs/koji-vs-fathom)\n- [AI Note-Takers for User Interviews](/docs/ai-note-taker-user-interviews)\n- [The Definitive Guide to AI Voice Interviews](/docs/ai-voice-interviews-definitive-guide)\n- [Structured Questions Guide](/docs/structured-questions-guide)\n- [Customer Discovery Interviews at Scale](/docs/customer-discovery-interviews-at-scale)\n","category":"Comparisons","lastModified":"2026-05-29T03:18:16.003544+00:00","metaTitle":"Koji vs Granola: AI Interviewer vs AI Notetaker (2026 Comparison)","metaDescription":"Granola is an AI meeting notetaker; Koji is an AI interviewer that runs and analyzes interviews at scale. Compare features, use cases, and when to use each — or both.","keywords":["koji vs granola","granola alternative","ai notetaker vs ai interviewer","granola for user research","ai meeting notetaker research","automated customer interviews","granola ai research","scale user interviews"],"aiSummary":"Granola is an AI notetaker that captures meetings you attend; Koji is an AI interviewer that conducts and analyzes interviews at scale. Choose Granola to improve notes on calls you join; choose Koji to run more interviews than you can personally attend. Many teams use both.","aiPrerequisites":["Basic familiarity with how AI meeting notetakers work","An interest in scaling customer or user interviews"],"aiLearningOutcomes":["Explain the difference between an AI notetaker and an AI interviewer","Decide when Granola is the right tool and when it falls short for research","Understand how Koji conducts and aggregates interviews automatically","Combine Granola and Koji in a single research workflow"],"aiDifficulty":"beginner","aiEstimatedTime":"8 minutes"}],"pagination":{"total":1,"returned":1,"offset":0}}