Multi-source study aid and visual summary workspace

For

Teachers, tutors and content teams producing study aids from articles, videos and question sets

Solves

Study material is scattered across several subscriptions and manual reformatting, so turning source content into visual summaries and review cards takes repeated effort.

Delivers

Editor-approved visual summaries and Q&A card sets linked to source references

Built in

about 5 weeks of creation time, MVP in 6 days

Investment

$13,500 for the MVP, $46,000 for the full product

Run it

Inside your business, or as part of your offer to clients

Reduce the manual work of turning source content into reviewed study aids while keeping sources and editorial judgment with the owner.

1. Ingest articles, permitted video links and question sets.
2. Generate visual summaries as mind maps, timelines, tables or cards.
3. Generate question-and-answer cards from articles.
4. Add question-driven multi-perspective insights.
5. Summarize permitted videos with timestamps.
6. Summarize web pages through a browser extension.
7. Save and share insights across devices.
8. Process images inside PDFs.
9. Select story formats such as comparisons, step-by-step cards or collections.
10. Present swipeable image-first cards with short media.
11. Synthesize multiple sources into one story with context and quotes.
12. Offer inline refinements to narrow or deepen results.
13. Build AI-driven mind maps from complex information.
14. Deconstruct complicated ideas into visual explanations.
15. Provide a media kit for presentations and sharing.
16. Analyze online articles and identify relevant information with NLP.
17. Tailor Q&A card formats to learning preferences.
18. Compare the reviewed result with the recorded baseline and value assumptions.
19. Capture corrections and named-owner approval before publication.
20. Export a versioned editor-approved study-aid set with source references and unresolved questions.

Everything these tools do, in one app

• AI-generated visual summaries Automatically creates visual formats like mind maps, timelines, tables, or cards from content.Found in Recap, Superus
• Q&A card generation Generates question-and-answer cards from articles to aid review and comprehension.Found in Read Pilot
• Multi-perspective insights Provides question-driven insights that encourage deeper exploration of content.Found in Recap
• YouTube integration Summarizes YouTube videos and provides timestamping.Found in Recap
• Chrome extension summarization Instantly summarizes articles and web pages via a browser extension.Found in Recap
• Saving and sharing Allows easy saving and sharing of insights across devices and with others.Found in Recap
• Image-based PDF support Planned feature to process images within PDFs.Found in Recap
• Generative story formats Selects story formats like comparisons, step-by-step cards, or collections based on inferred intent.Found in Heywa
• Swipeable image-first cards Presents content as swipeable cards with multiple images and occasional short media.Found in Heywa
• Multi-source orchestration Synthesizes multiple sources into a single story with context and quotes.Found in Heywa
• Inline refinements Offers action prompts to narrow results or jump to deeper comparisons without rewriting queries.Found in Heywa
• AI-driven mind maps Uses AI to transform complex information into intuitive, map-like diagrams.Found in Superus
• Enhanced concept visualization Helps deconstruct and understand complicated ideas by presenting them visually.Found in Superus
• Media kit access Provides access to a media kit for integrating visuals into presentations or sharing.Found in Superus
• Automated content analysis Analyzes online articles automatically to extract key information.Found in Read Pilot
• Advanced NLP Uses advanced natural language processing to accurately identify relevant information.Found in Read Pilot
• User-friendly interface Offers an easy-to-navigate interface for all skill levels.Found in Read Pilot, Superus
• Customizable card formats Allows tailoring of Q&A card formats to individual learning preferences.Found in Read Pilot

What goes in, what comes out

The workflow

1. In
   Start with

   Licensed articles, permitted video links, question sets and curriculum constraints

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect licensed articles

4. 3

   Permitted video links

5. 4

   Question sets and curriculum constraints

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Editor-approved visual summaries and Q&A card sets linked to source references

AI does the heavy lifting, people stay in charge

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. One fixed source set and licensed media; final curriculum and accuracy checks remain editorial. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Source intake and rights, Editable study-aid preview, Client proof and delivery. Use a thumbnail gallery for source sets, a large central editing canvas, and a right-hand panel for sources, constraints and comments. Let users compare versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant card or diagram. Make the task-specific outcome editor-approved visual summaries and Q&A card sets linked to source references visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, source versions, client comments, approval states, usage allowances, revision limits, download history and a rights record for supplied material. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.

Integrations and data access

Author-owned articles, permitted video links and licensed question sets. Cloud asset storage, document import/export and learning-platform 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.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   6 days

   One buyer segment, one recurring use case; first modules: ingest articles, permitted video links and question sets; generate visual summaries as mind maps, timelines, tables or cards. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   7 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   3 weeks

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will teachers, tutors and content teams producing study aids from articles, videos and question sets use it to solve "study material is scattered across several subscriptions and manual reformatting, so turning source content into visual summaries and review cards takes repeated effort"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Accepted study aids per editorial hour and corrections after publication.
4. Measure, then decide. Track accepted study aids per editorial hour and corrections after publication; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Pilot scope: One fixed source set and licensed media; final curriculum and accuracy checks remain editorial. Implement one approved input format, a bounded representative case set and the first two task modules: ingest articles, permitted video links and question sets; generate visual summaries as mind maps, timelines, tables or cards. Support the third module with operator review: generate question-and-answer cards from articles. 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.

After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around editor-approved visual summaries and Q&A card sets linked to source references. Retain the explicit scope boundary: One fixed source set and licensed media; final curriculum and accuracy checks remain editorial.

What the build depends on. Asset upload and preview, asynchronous generation jobs, editable version history, reviewer access and tested export formats. High-fidelity production requires specialist curriculum QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One fixed source set and licensed media; final curriculum and accuracy checks remain editorial.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test a USD 300-1,500 fixed pilot for one defined source package. Offer a monthly production allowance after repeat demand. Quote complex media or specialist curriculum design separately. These are test prices, not market benchmarks. Package the initial sale as one bounded editor-approved visual summaries and Q&A card sets linked to source references. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.

Message to test

Reduce the manual work of turning source content into reviewed study aids while keeping sources and editorial judgment with the owner. Demonstrate a concrete editor-approved visual summaries and Q&A card sets linked to source references using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Teachers, tutors and content teams producing study aids from articles, videos and question sets professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample editor-approved visual summaries and Q&A card sets linked to source references from a small authorized input set, with a transparent calculation of accepted study aids per editorial hour and corrections after publication and no promised savings.

The first 30 days

1. Week 1: interview five teachers, tutors and content teams producing study aids from articles, videos and question sets and inspect a recent example of study material scattered across several subscriptions and manual reformatting.
2. Week 2: prepare a consented or synthetic demonstration of the three task modules.
3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
4. Week 4: measure accepted study aids per editorial hour and corrections after publication, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.

Paid pilot

Agree quality and outcome thresholds before the pilot using this measure: Accepted study aids per editorial hour and corrections after publication. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.

Success metrics

Accepted study aids per editorial hour and corrections after publication; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs editor-approved visual summaries and Q&A card sets linked to source references. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.

Why clients would pick it

A reusable library of approved study-aid formats, curriculum constraints and review examples, together with reliable delivery for a narrow education niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for teachers, tutors and content teams producing study aids from articles, videos and question sets. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Recap, Heywa, Superus and Read Pilot, plus manual reformatting and generic generation tools. Compare this product with the buyer's present method on accepted study aids per editorial hour and corrections after publication. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Generation attempts, video or image processing, storage, reviewer hours, client revision rounds and licensed source assets. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of editor-approved visual summaries and Q&A card sets linked to source references. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve source attribution, quotation accuracy and usage permissions. Teachers and editors approve substantive changes and publication scope. One fixed source set and licensed media; final curriculum and accuracy checks remain editorial. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.