Koji vs Enterpret (2026): AI Customer Interviews vs Feedback Intelligence

TL;DR: Enterpret is a customer feedback intelligence platform — it ingests the feedback you already collect (support tickets, app reviews, NPS verbatims, community posts) and uses AI to categorize it into an evolving taxonomy. Koji is an AI-native customer research platform — it runs moderated voice and chat interviews on demand, asks dynamic follow-ups, and codes themes across every conversation. Enterpret analyzes the past. Koji generates the future. They sit on opposite ends of the insight pipeline.

Quick answer: which one solves your problem?

• Choose Enterpret if you have a high volume of inbound feedback flowing in from Zendesk, Intercom, app stores, NPS, and Slack, and you need one place to aggregate, tag, and trend it.
• Choose Koji if you need to go ask customers something you do not have answers to yet — discovery, churn diagnosis, win/loss, concept tests, pricing reactions — and you want the AI to moderate the interviews and synthesize the themes.

Enterpret is a listening layer for feedback you are already receiving. Koji is a research engine for questions you have not asked yet. The difference matters: no amount of taxonomy can extract an answer from feedback nobody ever gave you.

What Enterpret actually does

Enterpret is a unified customer feedback intelligence platform. It connects to the channels where unsolicited feedback already lives — Zendesk, Intercom, Slack, Twitter/X, app store reviews, community forums, and NPS/CSAT survey verbatims — and consolidates them into a single source of truth. Its core strengths:

• Adaptive taxonomy. Enterpret builds a continuously evolving categorization that reclassifies feedback as your product language shifts, avoiding the quarterly taxonomy rebuilds that plague legacy text analytics.
• Context Graph. It connects each feedback signal to customer segment, lifetime value, lifecycle stage, and product area, so you can quantify which segments are asking for what.
• Sentiment and topic clustering, natural-language search, dashboards, alerts, and an MCP server that lets Claude or ChatGPT query the feedback corpus programmatically.

Enterpret does not publish pricing; it is a sales-led, enterprise-tier product. Industry reports peg annual contracts in the $30,000–$100,000+ range depending on data volume. Reviewers consistently praise its aggregation power but note a meaningful learning curve given the breadth of functionality.

The fundamental constraint: Enterpret can only analyze feedback that already exists. If your churned customers never wrote a ticket explaining why they left, that reason is invisible to any aggregation tool — there is nothing to aggregate.

What Koji does differently

Koji is built for the other half of the pipeline: generating primary research data that did not exist five minutes ago. You describe what you want to learn, and Koji's AI moderates async voice and chat interviews, asking real-time follow-up probes based on what each respondent says — not a fixed script.

• AI-moderated interviews at scale, in 30+ languages, with dynamic probing that digs into the why behind every answer.
• Six structured question types — open_ended, scale, single_choice, multiple_choice, ranking, and yes_no — so a single Koji study captures both the quantitative measure and the conversational reasoning behind it. (See the structured questions guide.)
• Automatic thematic analysis across every transcript in a study, with themes and patterns surfaced and supported by verbatim quotes.
• One-click reports and an AI consultant you can interrogate about your findings.
• An MCP server so you can launch studies and pull insights from Claude, Cursor, or your own tooling.

Koji is transparent and self-serve: Free (10 one-time credits), Insights at €29/month (29 credits), Interviews at €79/month (79 credits), and custom Enterprise. Credits are spent per conversation (1 for chat, 3 for voice, 5 for a report refresh), and a built-in quality gate means only conversations scoring 3+ ever consume a credit.

Head-to-head comparison

| Dimension | Enterpret | Koji | |---|---|---| | Category | Feedback intelligence (analyze existing feedback) | AI research platform (generate new interviews) | | Core input | Tickets, reviews, NPS, community, Slack | Customers answering moderated interviews | | Asks follow-up questions | No — it tags what was already said | Yes — real-time AI probing | | Structured + qualitative in one study | No | Yes — 6 question types | | Thematic analysis | Yes, across inbound channels | Yes, across interview transcripts | | Best for | VoC aggregation, trend monitoring | Discovery, churn, win/loss, concept/pricing tests | | Pricing | Sales-led, ~$30K–$100K+/yr | Free → €29 → €79 → custom | | Time to first insight | Days to weeks (integration + taxonomy) | Hours |

The real distinction: solicited vs unsolicited insight

This is the heart of the comparison. Enterpret is exceptional at making sense of unsolicited feedback — the steady stream customers volunteer through support and reviews. But unsolicited feedback is biased toward the loudest moments: bugs, outages, and billing complaints. It rarely tells you why a prospect chose a competitor, what nearly stopped someone from upgrading, or how a brand-new concept lands.

Koji produces solicited insight — you choose the question, the audience, and the moment. That is why teams run Koji for the high-stakes questions where waiting for inbound feedback is not an option: win/loss interviews, churn diagnosis, and pre-launch concept validation.

What the 2026 data says

The research function is becoming strategic, and speed is the differentiator:

• The share of organizations where research is essential to all levels of business strategy nearly tripled in a year — from 8% in 2025 to 22% in 2026 (Qualtrics 2026 Market Research Trends).
• 63% of teams cite time and bandwidth as their top research constraint, and 39% struggle to recruit participants in time (State of User Research 2026). AI-moderated interviewing directly attacks both.
• Customer interviews remain the #1 research method at 86% adoption, ahead of usability testing (84%) and surveys (77%) — primary conversations still beat passive listening.
• More than half of researchers (53%) now use AI regularly, and Qualtrics found teams not using AI are 4x more likely to lose organizational influence.

The takeaway: aggregating existing feedback is table stakes. The strategic edge in 2026 comes from how fast you can ask a new question and get a synthesized, defensible answer — which is exactly Koji's design center.

Do you need both?

Often, yes — and they do not overlap. Keep Enterpret as the always-on listening layer for inbound feedback at scale. Add Koji whenever you need to initiate a conversation: validate what the inbound data is hinting at, interview the churned accounts that never filed a ticket, or pressure-test a concept before you build it. Enterpret tells you what people are already saying; Koji lets you ask the question nobody has answered yet.

If you only have budget for one and you are a startup or a lean product team that does not yet have a firehose of inbound feedback, start with Koji — you can run real research this week for the price of a team lunch. If you are an enterprise drowning in inbound tickets and reviews, Enterpret earns its seat — and Koji becomes the scalpel for the questions aggregation cannot answer.

Try Koji free

Koji turns a research question into synthesized insight in hours, not weeks — no moderator, no recruiting agency, and no research expertise required. Run AI-moderated voice and chat interviews, capture structured and qualitative answers in one study, and get an auto-coded report with quotes you can act on. Start free with 10 credits and see the difference between analyzing feedback and generating it.