TL;DR: Insight7 analyzes call recordings after they happen. Koji runs the interviews itself: AI-moderated voice and text conversations with structured questions, automatic thematic analysis and one-click reports. You start free with 10 credits and no card, a text interview uses 1 credit and a voice interview 3, and only conversations that pass a quality check are charged. If your bottleneck is getting customer data (not just analyzing what you already have), Koji is the more complete platform.
The "AI customer research" category has split into two camps in 2026. One camp, typified by Insight7, sits after the interview and uses AI to process recordings. The other (Koji, Listen Labs, Strella) uses AI to run the interview itself, removing the human moderator entirely.
This guide compares the two side by side: what each does well, where each falls short, and which fits your team.
Quick comparison table
| Feature | Koji | Insight7 |
|---|---|---|
| AI runs interview live | Yes (voice + text) | No (analyzes recorded calls) |
| Structured questions | 6 types (open-ended, scale, single/multi-choice, ranking, yes/no) | Survey logic not core |
| Voice interviews | AI voice moderator with real-time follow-ups | Imports Zoom/Meet/Teams recordings |
| Recruits participants for you | Built-in panel + share link | You bring the calls |
| Automatic thematic analysis | One-click | One-click |
| How you pay | Credits: 1 per text interview, 3 per voice interview, only for conversations scoring 3+ on quality. Monthly plans include credits | Monthly tiers by number of call analyses (review sites list an entry tier around $19/month) |
| Free tier | 10 credits at signup, no card | Free trial or small free tier, depending on listing |
| Setup time to first study | ~15 minutes | Depends on call inventory |
| Best for | Founders, PMs, researchers who need new customer data | CS/Sales QA teams analyzing existing calls |
The fundamental difference: collection vs analysis
Insight7 is, at its core, a call analytics tool. The product imports recordings from Zoom, Google Meet and Microsoft Teams, transcribes them, and uses AI to surface themes, risks and coaching opportunities. It is powerful, but it assumes you already have the calls.
Koji starts one step earlier. The platform's AI-moderated interview engine actually conducts the conversation. A respondent clicks a link, speaks (or types) with an AI moderator, and the AI asks follow-up questions in real time based on what they say. Koji handles recruitment, moderation, transcription, analysis and reporting in a single workflow.
If you put both products on a customer research timeline, they sit in different places:
- Insight7 = transcribe → analyze → report
- Koji = recruit → moderate → transcribe → analyze → report
That extra "moderate" step is where most research-team operational pain lives: someone has to find people, book them and sit through every call before there is anything to analyze.
Pricing: side-by-side
Insight7 (as listed on G2 and Fitgap in 2026; Insight7 does not always publish a full price sheet, so confirm with them before budgeting):
- Starter: about $19/month, 1 user, around 10 call analyses
- Pro: about $99/month, 50 analyses
- Business: about $299/month, 3 users, 200 analyses, PII redaction
- Enterprise: custom
Koji (2026):
- Free: 10 credits at signup, no card required. That is enough for 10 text interviews or 3 voice interviews.
- Credits: a text interview uses 1 credit, a voice interview 3, and a report refresh 5.
- Only for what works: a conversation that scores below 3 out of 5 on quality is free and never charged.
- Paid plans include a monthly credit allowance, with credit top-ups when you need more. Current plans and prices are on the pricing page.
- Enterprise: custom committed volume.
Koji prices per interview it runs. Insight7's model charges per analysis of an existing call, which means the interview itself costs Insight7 nothing, but you have already paid for the moderator's time, recruiting and scheduling elsewhere. Once you factor in those external costs, Koji's all-in cost is typically lower, especially for teams without an in-house research function.
Feature comparison
Live AI moderation (Koji's biggest advantage)
Koji's voice interview is a real conversation. The AI listens, interprets and probes ("You mentioned the export feature was confusing. Can you tell me what specifically tripped you up?") without a human in the loop. The same study supports text-mode interviews for participants who prefer typing, and runs 24/7 with no scheduling.
Insight7 does not run interviews. You record calls separately (using Zoom, Gong, Otter or a moderator on your team), then upload them. If you do not have calls, Insight7 has nothing to analyze.
Structured questions
Koji supports six structured question types inside the same conversation: open-ended, scale, single-choice, multi-choice, ranking and yes/no. The AI moderator weaves them in mid-conversation, so a single Koji study can blend NPS scores, feature ranking and qualitative depth in one session. Traditional surveys (Typeform, SurveyMonkey) can't follow up on an answer, and pure conversation tools can't give you clean numbers; Koji does both.
Insight7 does not run surveys, so this category does not apply.
Analysis and reports
Both platforms produce one-click reports. Koji's report generator clusters every interview into themes, surfaces verbatim quotes, and produces an executive summary you can paste into a deck. Insight7's report focuses on call patterns, coaching tips and risk flags across many calls.
For a researcher running 30 customer discovery sessions, Koji's report is more useful (it answers "what did people say about pricing?"). For a CS leader QA-ing 500 support calls, Insight7's report is more useful (it answers "which agents are flagging compliance risks?").
Recruitment
Koji ships with built-in recruitment: generate a share link and distribute it via email or community, import your own customers for personal invite links, or describe your target audience and recruit from Koji's panel partners in 130+ countries, with the price per completed interview shown before you launch.
Insight7 has no recruitment layer. You source calls however you already source them.
Use cases: which tool fits which problem?
Choose Koji if you need to:
- Run customer discovery interviews for a new product (founders, PMs)
- Validate a feature with 30+ customers in under a week
- Replace static surveys with conversational research
- Run ongoing voice-of-customer programs with no research team
- Conduct exit interviews to understand churn at scale
Choose Insight7 if you need to:
- Analyze hundreds of recorded sales or support calls per month
- QA agent performance and compliance across a CS team
- Extract themes from existing call libraries you already own
The two tools are not strictly competitors; they are adjacent. Many teams use both: Koji to generate fresh customer conversations, Insight7 (or Gong, Avoma) to mine existing rep-led calls.
Why teams switch from Insight7 to Koji
The most common migration we see: a PM or founder buys Insight7, realizes the bottleneck was not analysis but actually getting customers on calls, and replaces it with Koji. Scheduling friction is what kills a weekly interview habit, and Koji's always-on share link removes it.
Three concrete advantages teams report after switching:
- No scheduling overhead. A Koji study is a link. The respondent self-serves whenever they want, day or night.
- Structured + qualitative in one study. Koji's six question types let you replace a Typeform survey and a Calendly call with a single 12-minute interview.
- Consistent moderation. Every participant gets the same questions asked the same way, with follow-ups on what they actually said. Insight7 still inherits the style and bias of whoever ran the original call.
Try Koji free
Sign up at koji.so and you get 10 free credits, enough to run 3 voice interviews or 10 text chats with no card on file. Most teams are running their first study within 15 minutes. If your research bottleneck is getting the data rather than processing what you already have, Koji is the modern, AI-native answer.
