AI app for science and research · no coding needed
Evidence-backed research and reporting workspace
Reduce the time from question to a cited, reviewable report while keeping sources and drafts in one owned workspace.
Made for: Research teams, analysts and knowledge workers who gather sources and produce evidence-backed reports
What it does for you
The problem
Topic research, source gathering and report writing are split across several rented tools, so citations, data and drafts are scattered and hard to verify.
What it gives you
Reviewer-approved evidence-backed report with linked citations
What you give it
Plain-language research questionsuploaded documentspermitted web sourceslive data sets
Build your own version of Researcher & Analyst in M365 Copilot, GPT Researcher and more
One app with what these 5 AI tools do, yours to keep and change: Researcher & Analyst in M365 Copilot, GPT Researcher, STORM, Iris.ai, DeepSeek-V3.1.
Everything these tools do, in one app
- Natural language query Allows users to ask questions in plain language to find relevant information quickly.Found in Researcher & Analyst in M365 Copilot
- Automated information gathering Automatically collects information on a given topic from various sources.Found in GPT Researcher, STORM
- Document upload and management Lets users upload and organize collections of research documents.Found in Iris.ai
- Web and local data sources Supports research from both online web sources and local documents.Found in GPT Researcher
- Live proxy data sets Connects to live data sets from publishers, patent authorities, or internal repositories.Found in Iris.ai
- Full-text search and filtering Enables full-text searches and contextual filtering to retrieve relevant documents quickly.Found in Iris.ai
- Automatic summarization Generates summaries of lengthy documents or data to highlight key points.Found in Researcher & Analyst in M365 Copilot, Iris.ai
- Multi-document summarization Produces summaries across multiple documents to simplify review.Found in Iris.ai
- Data analysis and trend interpretation Analyzes data to help interpret trends and patterns within datasets.Found in Researcher & Analyst in M365 Copilot
- Data extraction and organization Systematically extracts and organizes data from documents for analysis.Found in Iris.ai
- Report generation Compiles findings into structured reports or summaries.Found in GPT Researcher, STORM
- Deep research workflow Explores topics recursively, diving into subtopics while maintaining a holistic view.Found in GPT Researcher
- Customizable research parameters Allows users to tailor research depth, breadth, and domain-specific agents.Found in GPT Researcher
- Interactive curation Adjusts the curation process based on user needs to highlight relevant data.Found in STORM
- Real-time monitoring and alerts Monitors for new documents meeting specific criteria and alerts users.Found in Iris.ai
- Collaboration and sharing Enables sharing of insights and findings within teams.Found in Researcher & Analyst in M365 Copilot
- Export options Allows research outputs to be exported, such as PDF documents.Found in GPT Researcher
- Multi-step task handling Improves handling of complex, multi-step tasks and tool usage for stronger agent abilities.Found in DeepSeek-V3.1
- Hybrid inference modes Offers toggle between quick responses and deeper, multi-step reasoning.Found in DeepSeek-V3.1
- Large context window Supports extensive chats and reasoning tasks with a 128K token context length.Found in DeepSeek-V3.1
- Open-source weights Provides open-source model weights for community contributions and customization.Found in DeepSeek-V3.1
- Strict function calling API Supports beta API for strict function calling to integrate with external tools.Found in DeepSeek-V3.1
How it works, step by step
- Accept plain-language research questions
- Gather information automatically from permitted sources
- Upload and organize document collections
- Search both web and local documents
- Connect to live permitted data sets
- Run full-text search with contextual filters
- Summarize long documents
- Summarize across multiple documents
- Analyze data and interpret trends
- Extract and organize data from documents
- Generate structured reports with linked citations
- Run recursive deep research across subtopics
- Set research depth, breadth and domain parameters
- Adjust curation interactively to highlight relevant data
- Monitor for new matching documents and alert users
- Share findings and comments within teams
- Export reports to PDF and common formats
- Handle multi-step tasks with tool use
- Toggle between quick answers and deep reasoning
- Support long research sessions with a large context window
- 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 evidence-backed 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 Evidence-backed research 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 Evidence-backed research 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 links5 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare25 KB
- prompt-vps.mdThe same build on your own server (Docker)25 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria12 KB
- demo/index.htmlThe working demo on sample data199 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 the time from question to a cited, reviewable report while keeping sources and drafts in one owned workspace. For research teams, analysts and knowledge workers who gather sources and produce evidence-backed reports, convert a plain-language question, uploaded documents, permitted web sources and live data sets into a reviewer-approved evidence-backed report with linked citations. The benefit is a testable hypothesis, measured through accepted reports per research hour and corrections after review; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect the plain-language question, uploaded documents, permitted web sources and live data sets, then follow this sequence: 1. Accept plain-language research questions. 2. Gather information automatically from permitted sources. 3. Upload and organize document collections. 4. Search both web and local documents. 5. Connect to live permitted data sets. 6. Run full-text search with contextual filters. 7. Summarize long documents. 8. Summarize across multiple documents. 9. Analyze data and interpret trends. 10. Extract and organize data from documents. 11. Generate structured reports with linked citations. Resolve uncertain cases with qualified reviewers, approve the reviewer-approved evidence-backed report with linked citations, and measure accepted reports per research hour and corrections after review 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. Final source verification, interpretation and professional judgment 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 reviewers approve substantive claims and publication scope. One research domain and one approved source set; final source verification and interpretation 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 research domain and one approved source set; final source verification and interpretation remain human. Implement one approved input format, a bounded representative case set and the first modules: accept plain-language research questions; gather information automatically from permitted sources; upload and organize document collections; search both web and local documents; summarize long documents; summarize across multiple documents; generate structured reports with linked citations. Support the remaining modules with operator review. 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, permitted web sources and licensed data sets. Cloud document storage, reference managers, data repositories and report 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: Research brief and sources, Editable report workspace, Review and delivery. Use a project list with a large central report canvas and a right-hand panel for sources, extracted data, alerts and comments. Let users compare draft versions side by side and switch between quick and deep research modes. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant claim or source. Make the task-specific outcome reviewer-approved evidence-backed report with linked citations visible beside its evidence, review state and value baseline.
