{"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":"2026-06-01T07:56:55.416Z"},"content":[{"type":"documentation","id":"7df978db-b685-4616-a98b-e30f551d6bb6","slug":"koji-vs-read-ai","title":"Koji vs Read AI: AI Notetaker vs AI Customer Research Interviewer (2026)","url":"https://www.koji.so/docs/koji-vs-read-ai","summary":"Honest comparison of Read AI (AI meeting notetaker) and Koji (AI customer research interviewer). Different jobs, different stacks. Includes 2026 pricing, side-by-side feature matrix, and a use-both workflow for product, UX, and PMM teams.","content":"If you're comparing [Read AI](https://www.read.ai/) and Koji, you're really comparing two different jobs: passively capturing knowledge from meetings you'd be having anyway versus proactively running customer research at scale. Both use AI. Both produce summaries. But they sit in different parts of the GTM and product-discovery stack, and most teams that use one eventually want the other.\n\nThis guide walks through the differences honestly — pricing, features, what each one is built for, and a workflow for using them together.\n\n## TL;DR — at a glance\n\n- **Read AI** is an AI meeting assistant. It joins your Zoom, Meet, and Teams calls, transcribes them, generates summaries, surfaces action items, and links meeting content to related emails and CRMs. Founded in Seattle in 2021, it raised $81M across three rounds and was valued at $450M in its October 2024 Series B led by Smash Capital and Madrona. The company had roughly 110 employees as of April 2026.\n\n- **Koji** is an AI customer-research platform. It runs adaptive AI-moderated interviews (voice or text) with your customers, prospects, and lapsed users — at the speed of a survey, with the depth of a 1:1 interview. Where Read AI captures meetings you already have, Koji *creates* customer conversations you wouldn't otherwise be able to run.\n\nIf you sit in sales, CS, or revops and want better notes from internal calls, Read AI is the right tool. If you sit in product, UX, or PMM and want continuous insight from *customers* at scale, Koji is the right tool. Most modern teams use both.\n\n## What Read AI does\n\nRead AI joins your meetings as a bot, transcribes audio in real time, generates a structured summary, and identifies action items, topics, and key questions. It then connects that meeting intelligence to your inbox, Slack messages, CRM (Salesforce, HubSpot), and Notion to form what the company calls a \"personal knowledge graph.\" Read AI's positioning, per its own materials, is to be \"the independent system of record for productivity AI.\"\n\nStrengths:\n\n- Strong real-time meeting capture (engagement scoring, sentiment, video playback on higher tiers).\n- Integrations across the modern productivity stack — Slack and email search are bundled with paid plans, not gated behind enterprise.\n- Free tier (5 meetings/month) makes it easy to evaluate.\n- $19.75/mo Pro plan ($15/mo annual) brings unlimited meetings and 100 file uploads/month.\n\nLimits:\n\n- It records what's said in meetings you already have. It doesn't recruit research participants, design discussion guides, run unmoderated interviews, or produce synthesized findings across hundreds of customer voices.\n- The \"knowledge graph\" is built from *internal* signal (your emails, your calls, your CRM). It's not a customer-research repository in the qualitative-research sense.\n- For VoC, discovery, churn, or pricing research, you're still booking and running 1:1 interviews manually — Read AI just transcribes them better than Otter does.\n\n## What Koji does\n\nKoji is built for product, UX, PMM, and founders who need to interview real customers — proactively, repeatedly, and at scale.\n\nThe mechanics are different from a meeting notetaker:\n\n- You publish a [structured AI-moderated interview](/docs/how-ai-interviewers-work) link (voice, text, or both) using 6 question types: open_ended, scale, single_choice, multiple_choice, ranking, yes_no. See the [structured questions guide](/docs/structured-questions-guide).\n- Customers self-serve through the interview asynchronously — no scheduled Zoom, no human moderator, no scheduling overhead.\n- Koji's AI moderator probes adaptively — when a respondent says \"the onboarding was confusing,\" the moderator asks *what* was confusing, *when*, and *what they did about it.*\n- 100+ interviews are synthesized automatically: themes, verbatim quotes, quality scores (1–5), and a finished report — what a human analyst would spend a week on.\n- Custom AI consultants can be tuned to brand, vertical, and competitive set so the moderator's probes are domain-aware.\n\nWhere Read AI's sweet spot is internal meeting knowledge, Koji's sweet spot is structured outside-in customer discovery at the speed of a survey.\n\n## Side-by-side comparison\n\n| Dimension | Read AI | Koji |\n|---|---|---|\n| **Primary job** | Capture internal meetings | Run proactive customer research |\n| **Input** | Zoom / Meet / Teams calls you already host | Async AI-moderated interviews with customers |\n| **AI follow-up probing** | No (passive transcription) | Yes (adaptive moderator) |\n| **Recruitment / distribution** | None | Share link, CRM intercept, panel integrations |\n| **Structured question types** | N/A | 6 (open_ended, scale, single_choice, multiple_choice, ranking, yes_no) |\n| **Synthesis across many sources** | Search across meetings | Auto-themed reports across hundreds of interviews |\n| **Quality scoring per interaction** | Engagement score | 1–5 quality score per interview |\n| **Multilingual** | Limited | Yes (native interview in any language) |\n| **Best for** | Sales / CS / revops / PM standups | Product, UX, PMM, founders, market research |\n| **Free tier** | 5 meetings/mo | Available |\n| **Paid plans** | $15–$39.75 /mo per user | See Koji pricing page |\n\n## When to use Read AI vs Koji\n\n**Use Read AI when:**\n\n- You already host the conversations and just want them captured well.\n- The participants are your team, your prospects in active sales cycles, or known customers in scheduled QBRs.\n- You want to surface action items across an existing meeting cadence.\n- The downstream use is sales enablement or productivity, not synthesized customer research.\n\n**Use Koji when:**\n\n- You need 50–500 customer voices on a question and can't realistically schedule that many 1:1s.\n- The respondents are anonymous trial users, churned customers, or net-new prospects you don't have on the calendar.\n- You want a methodology that scales (Mom Test, JTBD switch interviews, ODI, concept testing, pricing research).\n- You want the analysis done — themed, quoted, and report-ready — without a week of manual coding.\n- You need multilingual coverage across markets without commissioning separate field firms.\n\nUse **both** when you want internal meeting knowledge in Read AI *and* a proactive customer-research engine in Koji feeding into the same insights repository.\n\n## Pricing snapshot (2026)\n\nRead AI's published plans:\n\n- **Free** — 5 meetings/month\n- **Pro** — $19.75/mo (or $15/mo annual) — unlimited meetings, 100 file uploads, integrations\n- **Enterprise** — $29.75/mo (or $22.50/mo annual) — video playback, highlights\n- **Enterprise+** — $39.75/mo, 10-user minimum — HIPAA, SSO\n\nKoji prices per study and seat (see the Koji pricing page) and includes the AI moderation, structured questions, synthesis, and reporting in one. Because Koji replaces the *combined cost* of an interview platform, transcription, a human analyst, and reporting, the apples-to-apples comparison is to legacy research firms — where a 20-person IDI study runs $10K–$30K at full service. AI moderation is typically 5–10% of that.\n\nSo the \"pricing\" question isn't really Read AI vs Koji — it's Read AI ($15–$40/seat/mo) vs Koji ($X/study) vs *the legacy research budget Koji replaces* ($10K–$30K per study). They're not substitutes for one another.\n\n## A \"use both\" workflow\n\nA common 2026 stack looks like this:\n\n1. **Read AI** captures sales calls, customer success QBRs, and PM stakeholder meetings.\n2. **Koji** runs continuous outside-in research: weekly discovery, monthly NPS follow-ups, quarterly pricing studies, churn deep-dives, concept tests.\n3. Both feed insights into a shared repository (Notion, Coda, or Koji's built-in insights dashboard) tagged by theme and customer segment.\n4. A weekly insights digest pulls \"what we heard *in* meetings\" (Read AI) alongside \"what we heard *from customers we proactively interviewed*\" (Koji).\n\nThe point isn't that one beats the other. The point is they answer different questions. Read AI tells you what was said in the room. Koji tells you what 200 customers think who never would have made it to the room.\n\n## How Koji compares to other AI notetakers\n\nIf you're evaluating Read AI alongside other notetakers, the same \"use both\" logic applies. Koji's other notetaker comparisons walk through the same framing for the closest competitors:\n\n- Read AI competes most directly with [Granola](/docs/koji-vs-granola), [Fathom](/docs/koji-vs-fathom), [tl;dv](/docs/koji-vs-tldv), and [Avoma](/docs/koji-vs-avoma) (Avoma being more on the conversation-intelligence side).\n- For dedicated AI interview platforms — the ones that, like Koji, are built for proactive customer research — see the [best AI interview software 2026](/docs/best-ai-interview-software-2026) guide.\n\n## Bottom line\n\nRead AI is an excellent AI meeting assistant — well-funded, fast-growing, and built into the productivity stack most teams already live in. It's the right answer for capturing meetings you already host.\n\nKoji is built for a different job: running structured, adaptive, multilingual AI customer-research interviews at a scale and cost that traditional research firms can't match. It replaces (or augments) the moderated-IDI line item on the research budget, not the meeting-notetaker one.\n\nThe right question for most teams isn't \"which one wins\" — it's \"do we have both jobs in our workflow?\" If you do, run both.\n\n## Related Resources\n\n- [Koji vs Granola](/docs/koji-vs-granola)\n- [Koji vs Fathom](/docs/koji-vs-fathom)\n- [Koji vs tl;dv](/docs/koji-vs-tldv)\n- [Koji vs Avoma](/docs/koji-vs-avoma)\n- [Best AI interview software 2026](/docs/best-ai-interview-software-2026)\n- [How AI interviewers work](/docs/how-ai-interviewers-work)\n- [Structured questions guide](/docs/structured-questions-guide)\n- [Conversation intelligence for customer research](/docs/conversation-intelligence-customer-research)\n\n*Sources: PitchBook, Crunchbase, and TLDL profiles for Read AI; Read AI public pricing page and product documentation (2026); CleverX and Maze 2026 Future of User Research Report for industry IDI cost comparison.*","category":"Comparisons","lastModified":"2026-06-01T03:22:21.694385+00:00","metaTitle":"Koji vs Read AI: Notetaker vs AI Interviewer (2026)","metaDescription":"Read AI captures meetings you already host; Koji runs proactive AI customer research. Pricing, features, and when to use both — full 2026 comparison.","keywords":["koji vs read ai","read ai alternative","ai notetaker vs ai interviewer","read ai vs koji","ai customer research vs meeting notetaker","read ai pricing 2026","ai meeting assistant comparison"],"aiSummary":"Honest comparison of Read AI (AI meeting notetaker) and Koji (AI customer research interviewer). Different jobs, different stacks. Includes 2026 pricing, side-by-side feature matrix, and a use-both workflow for product, UX, and PMM teams.","aiPrerequisites":["Basic familiarity with AI meeting assistants","Awareness of customer research workflows"],"aiLearningOutcomes":["Understand the structural difference between AI notetakers and AI customer research platforms","Decide when to use Read AI, when to use Koji, and when to use both","Compare 2026 pricing and feature sets head-to-head","Design a use-both workflow that captures both internal meeting knowledge and proactive customer insight"],"aiDifficulty":"beginner","aiEstimatedTime":"9 minutes"}],"pagination":{"total":1,"returned":1,"offset":0}}