Evidence-backed visual research synthesis workspace

For

Research teams, analysts and educators who turn documents, web pages and media into visual maps and study material

Solves

Insights and source material are scattered across papers, PDFs, videos and notes, so building cited visual maps and study outputs takes repeated manual work.

Delivers

Reviewer-approved visual maps, diagrams and study outputs linked to source citations

Built in

about 5 weeks of creation time, MVP in 6 days

Investment

$14,500 for the MVP, $49,500 for the full product

Run it

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

Reduce manual synthesis effort while keeping every claim traceable to its source.

1. Ingest documents, PDFs, web pages, media transcripts and pasted notes.
2. Extract citeable claims with source links.
3. Generate interactive mind maps and concept maps.
4. Build flowcharts, timelines and sequence diagrams from text or outlines.
5. Display 3D concept maps with interactive connections.
6. Break down charts and graphs into key trends.
7. Suggest content ideas and outlines from explored material.
8. Apply grammar and style corrections to generated text.
9. Offer customizable templates for maps, reports and study formats.
10. Generate flashcards, quizzes, study notes, essays and lesson plans from maps.
11. Support button-based interaction instead of complex prompts.
12. Aggregate knowledge sources such as Wikipedia, arXiv, PubMed, Semantic Scholar and YouTube.
13. Keep visual data current through scheduled source refresh.
14. Support real-time team collaboration and forking of shared insights.
15. Export maps as PNG or SVG and reports with citations.
16. Keep a history view of prior visual versions.

Everything these tools do, in one app

• AI content suggestions Provides AI-generated ideas and suggestions to inspire creativity and assist with writing.Found in Minduck
• Grammar and style corrections Offers real-time corrections for grammar and writing style.Found in Minduck
• Customizable templates Provides templates that can be customized for different writing formats.Found in Minduck
• Team collaboration Enables multiple users to work together on projects in real time.Found in Minduck, Heuristica
• Word processor integration Integrates with popular word processing software for a smoother workflow.Found in Minduck
• AI-powered analysis Uses AI to analyze information from sources and extract reliable, citeable insights.Found in ResearchFlow
• Visual mind mapping Generates interactive mind maps to visualize complex topics and relationships between ideas.Found in ResearchFlow, Heuristica, AI Mindmap Extension and 1 more
• Chart and graph breakdown Simplifies complex charts and graphs by highlighting key trends without requiring advanced data expertise.Found in ResearchFlow
• Automated research workflow Automates data collection and analysis to save time and streamline the research process.Found in ResearchFlow
• Simplified interaction Allows users to interact with AI by pressing buttons instead of writing complex prompts.Found in Heuristica
• Study material generation Transforms concept maps into study outputs such as flashcards, quizzes, study notes, essays, and lesson plans.Found in Heuristica
• Integrated knowledge sources Gathers information from multiple platforms like Wikipedia, arXiv, PubMed, Semantic Scholar, and YouTube in one place.Found in Heuristica
• Personalized learning Adapts the learning experience to the individual user.Found in Heuristica
• Content outline and summary generation Generates outlines or summaries based on the user's explorations.Found in Heuristica
• Instant flowchart generation Creates flowcharts instantly from text or outlines.Found in Infira
• Auto-building timelines Automatically arranges events and milestones into timelines.Found in Infira
• Interactive 3D concept maps Displays concept maps in 3D that reveal connections between ideas interactively.Found in Infira
• History view Allows users to revisit prior versions of their visuals.Found in Infira
• One-click conversion Converts web pages, PDFs, YouTube videos, and AI chats into mind maps with a single click.Found in AI Mindmap Extension
• AI-powered insights Uses AI to uncover patterns and generate ideas from content.Found in AI Mindmap Extension, Jumprun
• Integration with AI workspace Integrates with a larger AI-powered workspace for expanded brainstorming and exploration.Found in AI Mindmap Extension
• Information aggregation Collects data from diverse sources into one centralized platform.Found in Grimo AI
• Organization and distillation Organizes and refines data to capture the essence of notes and research.Found in Grimo AI
• Collaborative insights Allows users to fork (copy and customize) insights contributed by others for collaborative learning.Found in Grimo AI
• Query-over-search Uses a query-based approach to quickly extract relevant information without traditional search clutter.Found in Grimo AI
• Interactive canvases Provides dynamic canvases to visualize and engage with data interactively.Found in Jumprun
• Multi-source integration Aggregates information from various online platforms such as websites, YouTube, and social media.Found in Jumprun
• Continuously updated content Keeps visual data current by regularly updating content.Found in Jumprun
• PDF to mind map conversion Automatically converts PDF documents into structured mind maps.Found in Map This
• Multiple input options Allows users to generate maps from pasted notes or AI prompts in addition to PDFs.Found in Map This
• Downloadable output Saves generated mind maps as PNG or SVG files for easy sharing and future reference.Found in Map This
• User-friendly workflow Provides a streamlined process (e.g., upload, generate, save/share) for efficiency.Found in Map This
• Voice-based explanations Explains concepts through voice narration while visually illustrating ideas on a canvas.Found in Clevr
• Diagram generation Generates various diagrams such as flowcharts, timelines, and sequence diagrams.Found in Clevr
• Interactive conversation Allows users to ask follow-up questions or request clarifications during explanations.Found in Clevr
• Multi-language support Supports multiple languages for spoken interaction.Found in Clevr
• Canvas reset Provides an option to clear the canvas and restart explanations quickly.Found in Clevr

What goes in, what comes out

The workflow

1. In
   Start with

   Permitted documents, PDFs, web pages, media transcripts, knowledge-source queries and pasted notes

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect permitted documents

4. 3

   Web pages

5. 4

   Media transcripts and notes

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Reviewer-approved visual maps, diagrams and study outputs linked to source citations

AI does the heavy lifting, people stay in charge

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, citation checks and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Source access permissions, citation accuracy and final interpretation remain human responsibilities. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Source intake and permissions, Editable synthesis canvas, Review and export. Use a thumbnail gallery for projects, a large central canvas for maps, diagrams and timelines, and a right-hand panel for sources, citations, 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 node. Make the task-specific outcome reviewer-approved visual maps, diagrams and study outputs linked to source citations visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, source versions, citation records, 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 documents, permitted web pages and licensed knowledge sources. Cloud storage, reference managers, word processors and export 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 documents, PDFs, web pages, media transcripts and pasted notes; extract citeable claims with source links. 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 research teams, analysts and educators who turn documents, web pages and media into visual maps and study material use it to solve "insights and source material are scattered across papers, PDFs, videos and notes, so building cited visual maps and study outputs takes repeated manual work"?
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 visual maps per synthesis hour and corrections after review.
4. Measure, then decide. Track accepted visual maps per synthesis hour and corrections after review; 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 source set and one output family; citation accuracy and final interpretation remain human responsibilities. Implement one approved input format, a bounded representative case set and the first two task modules: ingest documents, PDFs, web pages, media transcripts and pasted notes; extract citeable claims with source links. Support the third module with operator review: generate interactive mind maps and concept maps. 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 reviewer-approved visual maps, diagrams and study outputs linked to source citations. Retain the explicit scope boundary: One source set and one output family; citation accuracy and final interpretation remain human responsibilities.

What the build depends on. Source upload and preview, asynchronous generation jobs, editable version history, reviewer access and tested export formats. High-fidelity synthesis requires specialist research QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One source set and one output family; citation accuracy and final interpretation remain human responsibilities.

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 synthesis allowance after repeat demand. Quote complex media, 3D or specialist research support separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewer-approved visual maps, diagrams and study outputs linked to source citations. 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 manual synthesis effort while keeping every claim traceable to its source. Demonstrate a concrete reviewer-approved visual maps, diagrams and study outputs linked to source citations using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Research teams, analysts and educators professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample reviewer-approved visual maps, diagrams and study outputs linked to source citations from a small authorized input set, with a transparent calculation of accepted visual maps per synthesis hour and corrections after review and no promised savings.

The first 30 days

1. Week 1: interview five research teams, analysts and educators and inspect a recent example of insights and source material scattered across papers, PDFs, videos and notes.
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 visual maps per synthesis hour and corrections after review, 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 visual maps per synthesis hour and corrections after review. 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 source 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 visual maps per synthesis hour and corrections after review; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs reviewer-approved visual maps, diagrams and study outputs linked to source citations. 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 source sets, citation rules and review examples, together with reliable delivery for a narrow research niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for research teams, analysts and educators. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Minduck, ResearchFlow, Heuristica, Infira, AI Mindmap Extension, Grimo AI, Jumprun, Map This and Clevr, plus manual note-taking and diagram tools. Compare this product with the buyer's present method on accepted visual maps per synthesis hour and corrections after review. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Model calls, media transcription, storage, reviewer hours, client revision rounds and licensed source access. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of reviewer-approved visual maps, diagrams and study outputs linked to source citations. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve source attribution, quotation accuracy and usage permissions. Named reviewers approve substantive interpretations and publication scope. One source set and one output family; citation accuracy and final interpretation remain human responsibilities. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.