AI app for science and research · no coding needed
Research evidence analysis and reporting workspace
Reduce analysis and reporting effort while keeping findings traceable to source.
Made for: Research teams analyzing calls, videos and datasets to produce evidence-backed findings
What it does for you
The problem
Research data sits in separate tools, so transcription, tagging, pattern analysis and reporting are manual and slow.
What it gives you
Reviewer-approved findings linked to source evidence
What you give it
Recorded callsvideo filestranscriptsstructured datasets
Build your own version of Notably, Looppanel and more
One app with what these 3 AI tools do, yours to keep and change: Notably, Looppanel, Profundo.
Everything these tools do, in one app
- Data Repository Consolidates and organizes all research data in one searchable place.Found in Notably, Looppanel
- AI-Powered Analysis Uses artificial intelligence to analyze data and extract insights.Found in Notably, Looppanel, Profundo
- Transcription Converts audio from calls and videos into text.Found in Notably, Looppanel
- Automatic Highlighting and Tagging Automatically highlights and tags important parts of research data.Found in Notably
- Cluster Analysis Groups data by theme, sentiment, or other criteria to identify patterns.Found in Notably
- Digital Sticky Notes Allows intuitive organization of ideas and findings using digital notes.Found in Notably
- Custom AI Templates Provides a library of templates for various research stages.Found in Notably
- Workflow Automation Automates tasks across the research workflow with an AI assistant.Found in Notably
- Call Recording Records calls for later analysis.Found in Looppanel
- Time-Stamped Notes Highlights key moments during recordings with time-stamped annotations.Found in Looppanel
- Clip Creation Creates clips of user behavior for focused analysis and sharing.Found in Looppanel
- Collaboration Enables teams to work together, share insights, and embed content in other applications.Found in Looppanel, Profundo
- Data Security Ensures research data is kept secure.Found in Looppanel
- Automated Pattern Recognition Automatically identifies trends and patterns in data.Found in Profundo
- Customizable Dashboards Provides personalized data visualization through dashboards.Found in Profundo
- Integration with Data Sources Connects with popular data sources and software tools.Found in Profundo
- Real-Time Data Processing Processes data in real time to provide up-to-date insights.Found in Profundo
How it works, step by step
- Consolidate calls, videos and datasets in one searchable repository
- Transcribe call and video audio into text
- Highlight and tag important passages automatically
- Group data by theme, sentiment or criteria
- Organize findings with digital sticky notes
- Apply custom AI templates for research stages
- Automate workflow steps with an AI assistant
- Record calls for later analysis
- Add time-stamped notes during recordings
- Create clips of user behavior for focused review
- Support team collaboration and embedded sharing
- Apply data security controls to research data
- Recognize trends and patterns across datasets
- Build customizable dashboards for visualization
- Connect to approved data sources and software tools
- Process incoming data in real time for current insights
- 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 findings report 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 Research evidence analysis and reporting workspace 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 Research evidence analysis and reporting workspace 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 Cloudflare28 KB
- prompt-vps.mdThe same build on your own server (Docker)28 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria14 KB
- demo/index.htmlThe working demo on sample data200 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 analysis and reporting effort while keeping findings traceable to source. For research teams analyzing calls, videos and datasets to produce evidence-backed findings, convert recorded calls, video files, transcripts and structured datasets into reviewer-approved findings linked to source evidence. The benefit is a testable hypothesis, measured through accepted findings per analyst hour and corrections after report approval; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect recorded calls, video files, transcripts and structured datasets, then follow this sequence: 1. Consolidate calls, videos and datasets in one searchable repository. 2. Transcribe call and video audio into text. 3. Highlight and tag important passages automatically. 4. Group data by theme, sentiment or criteria. 5. Organize findings with digital sticky notes. 6. Apply custom AI templates for research stages. 7. Automate workflow steps with an AI assistant. 8. Record calls for later analysis. 9. Add time-stamped notes during recordings. 10. Create clips of user behavior for focused review. 11. Support team collaboration and embedded sharing. 12. Apply data security controls to research data. 13. Recognize trends and patterns across datasets. 14. Build customizable dashboards for visualization. 15. Connect to approved data sources and software tools. 16. Process incoming data in real time for current insights. Resolve uncertain cases with qualified reviewers, approve reviewer-approved findings linked to source evidence, and measure accepted findings per analyst hour and corrections after report approval 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. One approved data-handling policy and consent scope; final interpretation and reporting decisions remain with qualified researchers. 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. Researchers approve substantive interpretations and publication scope. One approved data-handling policy and consent scope; final interpretation and reporting decisions remain with qualified researchers. 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 data-handling policy and consent scope; final interpretation and reporting decisions remain with qualified researchers. Implement one approved input format, a bounded representative case set and the first two task modules: consolidate calls, videos and datasets in one searchable repository; transcribe call and video audio into text. Support the third module with operator review: highlight and tag important passages automatically. 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
Participant-owned recordings, authorized transcripts and permitted research datasets. Cloud storage, call and video platforms, survey tools and reporting destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Data repository and import, Editable analysis workspace, Findings report and sharing. Use a thumbnail gallery for studies, a large central analysis canvas, and a right-hand panel for sources, tags and comments. Let users compare coded excerpts side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant excerpt. Make the task-specific outcome reviewer-approved findings linked to source evidence visible beside its evidence, review state and value baseline.
