AI app for science and research · no coding needed
Source-linked document reading and extraction workbench
Reduce time spent locating, reading and extracting document content while keeping every answer linked to its source.
Made for: Researchers, analysts and administrators who read and extract information from long PDFs and mixed document sets
What it does for you
The problem
Document answers, tables and citations are scattered across several rented tools, and extracted data cannot be traced back to the exact source passage.
What it gives you
Source-linked answers, summaries and extracted records with citations and structured exports
What you give it
Uploaded PDFsdocsspreadsheetsscanned files; licensed source material; extraction schemascolumn selections; review criteria
Build your own version of aiPDF, PDF Parser and more
One app with what these 7 AI tools do, yours to keep and change: aiPDF, PDF Parser, DeepTutor, AI Drive, PDF Dino, SciSpace by Typeset, Papermark AI.
Everything these tools do, in one app
- Interactive AI Chat Allows users to ask questions and receive instant answers based on the document content.Found in aiPDF, AI Drive, Papermark AI and 1 more
- Document Summarization Automatically generates concise summaries of lengthy documents.Found in aiPDF, AI Drive, Papermark AI
- Information Extraction Extracts specific data, details, or insights from documents.Found in aiPDF, PDF Parser, AI Drive and 2 more
- Multi-Format Support Handles various document types beyond PDFs, such as docs and Excel files.Found in aiPDF, AI Drive
- References and Citations Provides source references and citations to back up responses.Found in aiPDF
- PDF to JSON Conversion Converts PDF documents into structured JSON data for easy integration.Found in PDF Parser
- Drag and Drop Interface Simplifies uploading and processing of PDF files with an intuitive interface.Found in PDF Parser, PDF Dino
- Selective Column Extraction Allows users to choose specific columns or fields to extract from documents.Found in PDF Parser
- Batch Processing Processes multiple documents at once for efficiency.Found in PDF Parser
- Interactive Tutoring Engages users in dialogue-based learning sessions that adapt to responses.Found in DeepTutor
- Personalized Feedback Provides tailored feedback to help learners improve weak areas.Found in DeepTutor
- Multi-Subject Support Covers multiple academic subjects like math, science, and language arts.Found in DeepTutor
- Progress Tracking Monitors learning progress over time.Found in DeepTutor
- LMS Integration Integrates with common learning management systems.Found in DeepTutor
- Large File Handling Supports uploading and storing large PDF files up to 2GB.Found in AI Drive
- Long-Term Storage Allows document storage without time restrictions.Found in AI Drive
- Multi-AI Model Integration Accesses multiple leading AI models for document analysis.Found in AI Drive
- OCR Technology Converts images and scanned documents into searchable text.Found in AI Drive
- Secure Storage Provides encryption and secure management of sensitive documents.Found in AI Drive
- Customizable Memory Allows users to customize the AI's memory for document analysis.Found in AI Drive
- Table Extraction Extracts structured tables from PDF documents.Found in PDF Dino
- Multiple Output Formats Supports output in formats like CSV, JSON, and plain text.Found in PDF Dino
- Customizable Output Allows users to tailor the output to fit specific workflows.Found in PDF Dino
- Complex Content Decoding Simplifies confusing text, mathematical expressions, and tables in research papers.Found in SciSpace by Typeset
- Keyword-Free Search Enables finding relevant papers without specifying keywords.Found in SciSpace by Typeset
- All-in-One Research Platform Offers additional tools like Chat with PDF and AI Writer for academic tasks.Found in SciSpace by Typeset
- Pitch Deck to Memo Conversion Converts pitch decks into structured investment memos.Found in Papermark AI
- Content Improvement Tools Includes grammar checks and structural suggestions for documents.Found in Papermark AI
- Open-Source Platform Allows self-hosting, customization, and community contributions.Found in Papermark AI
How it works, step by step
- Upload PDFs, docs, spreadsheets and scanned files by drag and drop
- Run OCR on scanned pages to produce searchable text
- Ask questions and receive answers grounded in the document
- Generate concise summaries of long documents
- Extract named fields, details and insights
- Extract structured tables from pages
- Select specific columns or fields for extraction
- Convert documents into structured JSON
- Export results as CSV, JSON or plain text
- Attach source references and citations to every answer
- Process batches of documents in one run
- Decode complex text, formulas and tables in research papers
- Find relevant papers without specifying keywords
- Run dialogue-based tutoring sessions with personalized feedback
- Track learner progress across subjects
- Store large files long term under encryption and access controls
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned source-linked record 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 Source-linked document reading and extraction 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 Source-linked document reading and extraction 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 links5 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 data195 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 locating, reading and extracting document content while keeping every answer linked to its source. For researchers, analysts and administrators who read and extract information from long PDFs and mixed document sets, convert uploaded PDFs, docs, spreadsheets and scanned files into source-linked answers, summaries, extracted tables and structured exports under named-owner review. The benefit is a testable hypothesis, measured through accepted extracted records per reviewer hour and corrections after export; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect uploaded PDFs, docs, spreadsheets and scanned files, then follow this sequence: 1. Upload PDFs, docs, spreadsheets and scanned files by drag and drop. 2. Run OCR on scanned pages to produce searchable text. 3. Ask questions and receive answers grounded in the document. 4. Generate concise summaries of long documents. 5. Extract named fields, details and insights. 6. Extract structured tables from pages. 7. Select specific columns or fields for extraction. 8. Convert documents into structured JSON. 9. Export results as CSV, JSON or plain text. Resolve uncertain cases with qualified reviewers, approve source-linked answers, summaries and extracted records, and measure accepted extracted records per reviewer hour and corrections after export 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 document set and licensed source material; final interpretation and professional judgments 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 owners approve substantive changes and export scope. One approved document set and licensed source material; final interpretation and professional judgments 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 document set and licensed source material; final interpretation and professional judgments remain human. Implement one approved input format, a bounded representative case set and the first task modules: upload PDFs, docs, spreadsheets and scanned files by drag and drop; run OCR on scanned pages to produce searchable text; ask questions and receive answers grounded in the document; generate concise summaries of long documents; extract named fields, details and insights. Support the remaining modules with operator review: extract structured tables from pages; select specific columns or fields for extraction; convert documents into structured JSON; export results as CSV, JSON or plain text; attach source references and citations to every answer. 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
Author-owned documents, authorized interviews and permitted research sources. Cloud document storage, LMS platforms, reference managers 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.
The screens in detail
Primary screens: Document intake and library, Source-linked reading and chat, Extraction and export console, Administrator console. Use a thumbnail or list gallery for documents, a large central reading pane with a chat panel, and a right-hand panel for citations, extracted fields and review state. Let users compare answers side by side with the source passage. Display draft, changes requested and approved states. Provide a shared review link with comments anchored to the relevant page and passage. Make the task-specific outcome source-linked answers, summaries and extracted records visible beside its evidence, review state and value baseline.
