Complete AI Training

AI app for science and research · no coding needed

Research feed curation and briefing workbench

Reduce time spent scanning while keeping every claim traceable to its source.

Made for: Research leads, analysts and knowledge teams who must follow many sources without information overload

What Research feed curation and briefing workbench looks like
Open the demo For members · a working demo with sample data

What it does for you

The problem

Relevant articles and papers are scattered across many feeds, repeated across outlets, and too long to read, so important changes are missed and time is lost to scanning.

What it gives you

Reviewed daily briefing linked to original sources

What you give it

Licensed feedssaved searchesuser interest profilesfeedback

Build your own version of Feedly Leo, Waverly and more

One app with what these 3 AI tools do, yours to keep and change: Feedly Leo, Waverly, Soch.

Everything these tools do, in one app

  • AI-curated content feed Surfaces articles and research from many sources based on user interests.Found in Feedly Leo, Waverly, Soch
  • Personalized recommendations Adapts the feed to user preferences using feedback and shared links.Found in Feedly Leo, Waverly, Soch
  • Article summarization Condenses lengthy articles or papers into key points for quick reading.Found in Feedly Leo, Waverly, Soch
  • Content deduplication Removes repetitive news stories to prevent information overload.Found in Feedly Leo
  • Irrelevant content muting Filters out content that does not match user-specified interests.Found in Feedly Leo
  • Trainable AI Allows users to provide examples and feedback to refine recommendations over time.Found in Feedly Leo
  • Distraction-free reading Provides a focused reading interface that minimizes distractions.Found in Waverly
  • Annotation tools Enables note-taking and highlighting within articles for better retention.Found in Waverly
  • Platform integrations Connects with tools like Gmail, Salesforce, PowerPoint, Slack, and Teams to incorporate content into workflows.Found in Waverly
  • AI-generated visuals Creates visual aids to help ideas stick during quick scans.Found in Soch
  • Category selection Lets users choose from many categories to shape their feed.Found in Soch
  • Original source links Provides links back to original papers for verification and deeper reading.Found in Soch

How it works, step by step

  1. Ingest articles and papers from many permitted sources
  2. Rank items against stated interests and past feedback
  3. Adapt rankings from user feedback and shared links
  4. Summarize long articles and papers into key points
  5. Group duplicate stories covering the same event
  6. Mute items outside user-specified interests
  7. Accept examples and corrections to refine recommendations
  8. Provide a distraction-free reading view
  9. Support highlighting and notes inside items
  10. Generate simple visuals for quick scans
  11. Let users select categories that shape the feed
  12. Link every summary back to the original paper or article
  13. Compare the reviewed result with the recorded baseline and value assumptions
  14. Capture corrections and named-owner approval before sending briefings
  15. Export a versioned reviewed daily briefing linked to original sources 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 feed curation and briefing 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.

Sign in Become a member

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 feed curation and briefing workbench with you.

Have Nexibeo build it

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 Cloudflare24 KB
  • prompt-vps.mdThe same build on your own server (Docker)24 KB
  • spec.jsonData model, API, AI pipeline, acceptance criteria12 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 time spent scanning while keeping every claim traceable to its source. For research leads, analysts and knowledge teams who must follow many sources without information overload, convert licensed feeds, saved searches, user interest profiles and feedback into a reviewed daily briefing linked to original sources. The benefit is a testable hypothesis, measured through relevant items surfaced per review hour and briefing items later confirmed useful; do not assume that AI output alone produces business value.

Confirm the buyer's problem and scope, collect licensed feeds, saved searches, user interest profiles and feedback, then follow this sequence: 1. Ingest articles and papers from many permitted sources. 2. Rank items against stated interests and past feedback. 3. Summarize long articles and papers into key points. 4. Group duplicate stories covering the same event. Resolve uncertain cases with qualified reviewers, approve a reviewed daily briefing linked to original sources, and measure relevant items surfaced per review hour and briefing items later confirmed useful against a documented baseline.

How the AI works

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Summaries must stay traceable to the original item; final editorial judgment and interpretation remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

Safeguards

Preserve source attribution, quotation accuracy and usage permissions. Named editors approve substantive changes and briefing scope. One topic area and a fixed source list; summaries and rankings remain reviewable and every item links to its original source. 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 topic area and a fixed source list; summaries and rankings remain reviewable and every item links to its original source. Implement one approved input format, a bounded representative case set and the first two task modules: ingest articles and papers from many permitted sources; rank items against stated interests and past feedback. Support the third module with operator review: summarize long articles and papers into key points. 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

Publisher and repository feeds, saved searches, email digests and permitted research sources. Cloud storage, document import/export and briefing 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: Interest and source setup, Reviewed briefing, Item detail and archive. Use a feed list for sources, a central briefing canvas grouped by topic, and a right-hand panel for summaries, annotations and source links. Let users compare duplicate stories side by side. Display draft, changes requested and approved states. Provide a shareable briefing link with comments anchored to the relevant item. Make the task-specific outcome a reviewed daily briefing linked to original sources visible beside its evidence, review state and value baseline.