AI app for product development · no coding needed
Customer conversation insight and backlog workbench
Reduce manual feedback triage while keeping every insight linked to its source conversation.
Made for: Product and customer experience teams analyzing customer conversations and feedback
What it does for you
The problem
Customer conversations and feedback sit in separate tools, so insights, sentiment and backlog requests are extracted by hand and lose their evidence.
What it gives you
Reviewer-approved insights, categorized feedback and prioritized backlog requests linked to source evidence
What you give it
Permitted conversation recordingstranscriptssupport ticketssurvey responsesreview exports
Build your own version of User Evaluation, Inari and more
One app with what these 3 AI tools do, yours to keep and change: User Evaluation, Inari, impaction.ai.
Everything these tools do, in one app
- Conversation analysis Analyzes customer conversations and feedback to extract insights.Found in User Evaluation, Inari, impaction.ai
- AI-generated insights Automatically generates summaries and insights from data.Found in User Evaluation, Inari
- Sentiment evaluation Automatically evaluates customer sentiment.Found in Inari
- Feedback categorization Categorizes feedback into top requests, defects, praises, and learnings.Found in Inari
- Unified feedback hub Consolidates data from multiple sources into a single hub.Found in Inari
- Multi-source data support Works with various data sources like AWS S3, GCP BigQuery, PostgreSQL, MySQL.Found in impaction.ai
- Multilingual transcription Provides accurate transcriptions in over 57 languages.Found in User Evaluation
- Speaker detection Identifies different speakers in transcriptions.Found in User Evaluation
- Custom vocabulary Allows custom vocabulary for transcription accuracy.Found in User Evaluation
- Real-time trend visualization Provides dynamic visualizations of trends and product insights.Found in Inari
- Generative data visualizations Creates generative data visualizations to help digest trends and comparative analyses.Found in User Evaluation
- Research reports Generates detailed research reports and presentations.Found in User Evaluation
- Powerful search Equipped with an intuitive search toolkit to identify high-priority conversations and deep dive into data cohorts.Found in impaction.ai
- Columbus Copilot Provides guided analysis through Columbus Copilot.Found in impaction.ai
- Customized recommendations Offers customized recommendations.Found in impaction.ai
- Save, group, track conversations Allows users to save, group, and track conversations.Found in impaction.ai
- Backlog management integration Pushes insights and prioritized backlog requests to Slack, JIRA, and Linear.Found in Inari
- Seamless integration Integrates with over 100 applications.Found in User Evaluation
How it works, step by step
- Ingest conversations and feedback from connected sources
- Transcribe recordings in supported languages
- Detect and label speakers in transcripts
- Apply custom vocabulary for transcription accuracy
- Evaluate customer sentiment per conversation and segment
- Categorize feedback into requests, defects, praises and learnings
- Generate summaries and insights from analyzed data
- Consolidate all sources into one feedback hub
- Search and filter high-priority conversations and cohorts
- Visualize trends and comparative analyses
- Generate data visualizations for trend digestion
- Produce research reports and presentations
- Provide guided analysis through a copilot
- Offer customized recommendations from findings
- Save, group and track conversations
- Push prioritized backlog requests to Slack, JIRA and Linear
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned reviewer-approved insight set with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Customer conversation insight and backlog workbench with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Customer conversation insight and backlog workbench with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links3 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare26 KB
- prompt-vps.mdThe same build on your own server (Docker)26 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria12 KB
- demo/index.htmlThe working demo on sample data199 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce manual feedback triage while keeping every insight linked to its source conversation. For product and customer experience teams analyzing customer conversations and feedback, convert permitted conversation recordings, transcripts, support tickets, survey responses and review exports into reviewer-approved insights, categorized feedback and prioritized backlog requests linked to source evidence. The benefit is a testable hypothesis, measured through accepted insights per analyst hour and backlog items traced to source evidence; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect permitted conversation recordings, transcripts, support tickets, survey responses and review exports, then follow this sequence: 1. Ingest conversations and feedback from connected sources. 2. Transcribe recordings in supported languages. 3. Detect and label speakers in transcripts. 4. Apply custom vocabulary for transcription accuracy. 5. Evaluate customer sentiment per conversation and segment. 6. Categorize feedback into requests, defects, praises and learnings. 7. Generate summaries and insights from analyzed data. 8. Consolidate all sources into one feedback hub. 9. Search and filter high-priority conversations and cohorts. 10. Visualize trends and comparative analyses. 11. Generate data visualizations for trend digestion. 12. Produce research reports and presentations. 13. Provide guided analysis through a copilot. 14. Offer customized recommendations from findings. 15. Save, group and track conversations. 16. Push prioritized backlog requests to Slack, JIRA and Linear. Resolve uncertain cases with qualified reviewers, approve reviewer-approved insights, categorized feedback and prioritized backlog requests linked to source evidence, and measure accepted insights per analyst hour and backlog items traced to source evidence against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Supported languages, custom vocabulary and source connectors remain bounded; final categorization and backlog priority decisions remain human. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve participant consent, source attribution, quotation accuracy and usage permissions. Named reviewers approve substantive categorizations and backlog priorities. One approved source set, one supported language and one backlog destination; final categorization and priority decisions remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One approved source set, one supported language and one backlog destination; final categorization and priority decisions remain human. Implement one approved input format, a bounded representative case set and the first two task modules: ingest conversations and feedback from connected sources; transcribe recordings in supported languages. Support the remaining modules with operator review: speaker detection, custom vocabulary, sentiment evaluation, feedback categorization, insight generation, unified hub, search, trend visualization, generative visualizations, research reports, copilot guidance, recommendations, conversation tracking and backlog push. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Customer-owned conversation recordings, authorized support tickets, survey responses and review exports. Cloud storage, data warehouses, backlog tools and messaging destinations. Start with file exchange and validate destination specifications before promising direct backlog writes. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Source and consent setup, Analysis workspace, Insight and backlog review. Use a thumbnail gallery for projects, a large central analysis canvas, and a right-hand panel for sources, categories and comments. Let users compare cohorts and time periods side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant conversation. Make the task-specific outcome reviewer-approved insights, categorized feedback and prioritized backlog requests linked to source evidence visible beside its evidence, review state and value baseline.
