ConceptSaaS product
Researchora
An AI-assisted research community: discover, publish, discuss and follow research in one place.
This is a concept page. The link above is an early version, not a finished product. The source is available to inspect.
- IdeaNo ventures at this stage
- ResearchNo ventures at this stage
- ValidationNo ventures at this stage
- PrototypeNo ventures at this stage
- MVPResearchora
- LaunchNo ventures at this stage
- GrowthNo ventures at this stage
The problem
Research work is spread across separate tools for finding papers, keeping track of reading, discussing ideas and sharing results. Switching between them costs time and context.
Who it's for
- Researchers and students who read and share papers
- Communities built around a research topic
Proposed solution
A single workspace that combines research discovery, post publishing, discussion, reading history, following and an AI assistant for exploring a topic.
What it includes
- Research discovery feed
- Post composer for publishing research posts
- AI assistant for research questions
- Interactive AI demo
- Reading history and following
- Supabase-backed accounts and profiles
- Responsive layout with light and dark mode
Technology
Next.js 16 · React · Tailwind CSS · Framer Motion · Supabase · Flask (optional API)
Milestones
Done
- Frontend-first prototype published on GitHub
- Posts and profiles schema for Supabase
- AI assistant route with a matching Python API
Next milestones haven’t been published.
Opportunity research
How I’m evaluating this. Assumptions are marked as assumptions; anything marked verified links to its source. No market sizes or projections appear here unless they are sourced.
Who experiences the problem
- People who regularly read papers and want to discuss or share them
What exists today
- Reference managers. Organise a personal library of papers.
- Academic social networks. Profiles, sharing and following between researchers.
- AI paper-search tools. Question answering and discovery across the literature.
Categories only. No claims are made about specific competitors.
Where the opportunity might be
- One place where discovery, discussion and AI-assisted reading share the same context
What this depends on
- AssumptionResearchers would rather use one workspace than separate tools for discovery, reading lists and discussion.
- AssumptionAn in-context AI assistant is valuable enough to bring people back regularly.
- AssumptionA new community can reach useful activity without an existing audience to seed it.
Risks
- A community product is only useful once enough people are active on it
- Established tools already hold researchers' libraries and networks
- AI answers about research must be accurate to be trusted
Validation steps
- DoneBuild a working prototype of the core experience
- To doInterview researchers about their current workflow
- To doTest the prototype with a small group around one topic
Customer discovery questions
- Where do you currently find papers worth reading, and what is frustrating about it?
- When you want to discuss a paper, where does that conversation happen today?
- What would make you move your reading list to a new tool?
Monetization
No monetization model has been decided.
Agents in this venture
- Researchora AssistantPrototype
The AI assistant inside Researchora, for asking research-related questions.
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