Quick answer: Koji and Reduct sit on opposite ends of the research workflow. Reduct is a transcription-and-video-analysis tool — you bring recordings you have already collected, and it helps you transcribe, search, tag, and clip them. Koji is an AI-native customer research platform that collects the conversations for you: it runs AI-moderated voice and text interviews around the clock, then automatically transcribes, themes, and reports on them. If your bottleneck is recruiting and actually running interviews — not just editing footage — Koji replaces the entire pipeline. Reduct only accelerates the analysis of calls you already managed to schedule, moderate, and record.
The core difference: collection vs. cleanup
Reduct is excellent at what it does. It delivers around 94% AI transcription accuracy (and up to 99% with human transcription), supports 90+ languages, and gives researchers a polished surface for tagging, clipping, and collaborative searching across video. Plans start at $15/month for individuals and around $75/seat/month for teams.
But notice the hidden assumption: you have to conduct every interview yourself first. Reduct does nothing to recruit participants, schedule sessions, moderate the conversation, or probe for depth. A researcher still spends the bulk of their week on logistics — and most teams never run enough interviews to reach saturation because human moderation simply does not scale.
Koji removes that constraint. You write a brief, Koji generates an interview plan, and an AI moderator conducts unlimited voice or text interviews simultaneously — 24/7, in dozens of languages. The output is the same artifact Reduct produces (clean transcripts, tagged themes, highlight clips) but Koji generates it automatically as a byproduct of running the study, not as a separate manual project.
The fastest growing research teams in 2026 are not the ones who tag transcripts faster. They are the ones who never had to manually run the interview in the first place.
Side-by-side comparison
| Capability | Reduct | Koji |
|---|---|---|
| Recruits & schedules participants | No | Yes (link, panel, or API) |
| Conducts the interview | No — you moderate | Yes — AI voice & text moderator |
| Adaptive follow-up probing | No | Yes — dynamic, per-answer |
| Transcription | Yes (94–99%) | Yes — automatic, built-in |
| Thematic analysis | Manual tagging | Automatic themes + sentiment |
| Structured + quant questions | No | Yes — 6 question types |
| One-click report | No | Yes — shareable insight report |
| Runs 24/7 at scale | No (1 call at a time) | Yes (unlimited concurrent) |
| Moderator bias | Present | Eliminated — consistent AI |
Where Koji pulls ahead: structured questions
Reduct treats every interview as unstructured video to be tagged after the fact. Koji lets you mix qualitative depth with quantitative rigor inside the same conversation using six structured question types: open_ended, scale, single_choice, multiple_choice, ranking, and yes_no.
That means a single Koji study can return a thematic narrative ("why customers churn") and a clean distribution chart ("how they rate onboarding 1–10") and a ranked list of most-wanted features — all auto-aggregated. In Reduct, the qualitative side requires manual tagging and the quantitative side does not exist at all; you would need a separate survey tool and a spreadsheet to stitch it together. Koji's report does it in one click. (See how Koji analyzes AI-moderated interview results and the AI transcript analysis guide.)
Speed: hours vs. weeks
The traditional pipeline — recruit, schedule, moderate, record, upload, transcribe, tag, synthesize — takes most teams two to six weeks per study. Reduct compresses the transcribe-and-tag steps. Koji compresses all of them.
Because Koji's AI moderator runs every interview in parallel, a study that would take a human researcher three weeks of back-to-back calls completes overnight. Insights arrive in hours, not weeks — with no research expertise required to launch. For continuous discovery teams, that is the difference between "we interviewed five customers last quarter" and "we interview five customers every week." (More on this in our continuous discovery handbook.)
Where Reduct still makes sense
To be fair: if your workflow is built around large volumes of pre-existing video — field ethnography, recorded sales calls, long-form documentary research, or footage you must edit for stakeholder reels — Reduct's video editor and human-transcription option are genuinely strong, and Koji is not a video editor. Some agencies pair the two: Koji to collect and analyze net-new interviews at scale, a tool like Reduct to clean up legacy archive footage. But for the core job most product, research, and marketing teams have in 2026 — get real customer insight fast and repeatedly — Koji owns the whole loop, and Reduct owns only the back half.
Pricing reality check
Reduct's $15 individual plan looks cheap until you add the true cost: a researcher's salary to run every interview by hand, recruiting fees, and weeks of calendar time. Koji's credit-based pricing (Insights at €29/mo, Interviews at €79/mo, Enterprise custom) bundles collection and analysis. Text interviews cost 1 credit, voice 3, and a report refresh 5 — and a quality gate means only conversations scoring 3+ consume credits, so you never pay for junk responses. The all-in cost per validated insight is dramatically lower when the platform also does the interviewing.
A real-world scenario: 50 interviews in a week
Picture a product team trying to understand why activation stalls. The Reduct path: a researcher books 50 calls (most prospects ghost, so they invite 120), runs two or three interviews a day for three weeks, uploads each recording, waits on transcription, then spends days tagging and clipping before writing up findings. Elapsed time: roughly a month — and the insight is stale the moment the next release ships.
The Koji path: the team writes a brief, Koji drafts the interview plan, and a shareable link goes to 200 recent signups. The AI moderator interviews everyone who clicks — in parallel, on their own schedule, with adaptive follow-ups that dig into why each person stalled. By the next morning there are 50+ completed interviews, already transcribed, themed, and sentiment-scored, with a one-click report surfacing the top three activation blockers and the verbatim quotes behind each. Elapsed time: overnight.
Same deliverable, radically different cost in human hours and calendar time. And because the marginal cost of the next study is near zero, the team re-runs it every release instead of once a quarter — turning research from a project into a habit. That is the structural reason AI-native platforms are displacing analysis-only tools: the bottleneck was never tagging speed, it was getting enough conversations in the first place. (See why AI interviewers are the future of customer research.)
The bottom line
Choose Reduct if your only problem is transcribing and tagging video you have already recorded. Choose Koji if your real problem — like most teams — is getting enough high-quality interviews in the first place, then turning them into shareable insight without a manual synthesis marathon. Koji is the AI-native option that replaces the entire research pipeline; Reduct is a legacy-friendly tool for the analysis step alone.
Ready to stop editing transcripts and start generating insight? Launch your first AI-moderated study on Koji — from question to insight in hours, no research team required.
