Night-time temperature is a stronger predictor of heat-related risk in dense urban settings.
Research workspace with contextual AI
Plan, evidence and write your research.All in one place.
SciCollab is a workspace for researchers, graduate students and scientific teams. It connects the whole study — from the first question and sources to analysis, collaboration and an IMRaD manuscript.
Start with one project. No card required.
- One research context
- AI under your control
- Individual and team work
Inside one SciCollab projectUrban heat and public health
ZAEvidence → Finding → ManuscriptHow does night-time heat exposure affect health risk across city districts?
The association remains after adjustment for density and baseline vulnerability.
Night-time heat exposure showed the strongest association in densely built districts.
SciCollab in 15 seconds
What is it?
A single workspace for the full research cycle.
Who is it for?
Researchers, graduate students, supervisors and teams.
What is inside?
Research design, evidence, methods, data, findings, manuscript and AI.
The hidden cost of fragmented research
Files are saved. Context is not.
Research rarely breaks because a document disappears. It breaks because the relationship between a decision, its evidence, the analysis and the final claim becomes impossible to reconstruct.
01Research question02PDF library03Methods document04Data table05Team chat06Manuscript
Six tools. One study. No shared research memory.
What changes with SciCollab
Not another folder for files. A connected model of the study.
The project becomes the system of record. Every important object stays in context, so the team can move forward without rebuilding the logic of the study.
Intent remains visible
Questions, hypotheses and objectives stay connected to the work they guide.
Claims retain support
Evidence fragments and exact locators remain attached to the claims they support.
Findings keep their lineage
Trace the path from a dataset and analysis to a finding and manuscript section.
One continuous research journey
Move through the study without rebuilding context at every stage.
Each workspace is structured for its task. The project preserves the links between them.
Frame
Define the problem, gap, question, objectives, hypotheses and intended contribution.
Ground
Build a verified evidence base and attach precise fragments to the work they support.
Design
Document study design, sampling, variables, instruments, ethics and the analysis plan.
Analyze
Register datasets and analyses, then capture findings with confidence and provenance.
Write
Develop an IMRaD manuscript without losing citations, decisions, versions or project context.
Prepare
Review gaps and assemble a portable publication and reproducibility package.
A workspace shaped around scientific work
The right structure appears when you need it.
SciCollab does not force the whole study into one giant form. Each stage has a focused workspace, while the project keeps the scientific logic connected.
01Problem and context
02Research gap
03Questions and hypotheses
04Contribution
01
Turn an idea into an explicit research design
Keep the gap, question, objectives, hypotheses and contribution visible in one canvas.
01Verified source
02Exact fragment
03Locator and note
04Linked research object
02
Work with evidence at the level of the claim
Capture exact fragments, locators and notes instead of collecting an unsearchable pile of PDFs.
01IMRaD structure
02Linked citations
03Version history
04Review before acceptance
03
Write with the project context beside the draft
Bring findings, evidence and decisions into an IMRaD manuscript with explicit review.
Research Copilot · Early access
AI that works inside the research context — not instead of the researcher.
Copilot receives a bounded project context, shows the basis and limitations of its proposal, and leaves every material change for the researcher to review.
Context
The task is grounded in the selected project objects.
Sources
Supporting evidence remains visible where the workflow provides it.
Limitations
Uncertainty and missing context are stated instead of hidden.
Control
AI proposes; the researcher accepts, edits or rejects.
−
The result was statistically significant.
+
The adjusted model showed an association, with uncertainty retained in the interpretation.
Collaboration with scientific memory
Keep teamwork inside the work it concerns.
Tasks, comments, decisions and versions stay next to the research objects they affect. New contributors can understand not only what changed, but why.
- Project roles and explicit access
- Discussion in the context of evidence, methods and drafts
- Responsibility, decisions and version history
One project, different responsibilities
Useful alone. Stronger with a team.
Researchers
Replace a fragmented personal workflow with one clear route through the study.
Graduate researchers
Turn supervision into visible decisions, evidence and next steps.
Research leads
See blockers, ownership and scientific gaps without status archaeology.
Institutions
Give research teams a common operating layer without taking ownership of their work.
From project work to a transferable result
Know what is ready — and what still needs attention.
Readiness checks surface missing links and incomplete research objects before handoff. Export is designed to keep the work useful beyond SciCollab.
Readiness & export is currently in early access. Direct transfer to Journalize is planned.Research design is explicit
ReadyFindings retain data and analysis lineage
ReadyClaims have supporting evidence
ReadyManuscript gaps are visible
ReviewWhy one connected workspace matters
Keep your specialist tools. Stop making the researcher carry all the context between them.
| Research work | A fragmented toolchain | SciCollab |
|---|---|---|
| Research question | Separate document | Part of the project model |
| Evidence | PDFs and references | Sources, fragments and claim links |
| Method decisions | Document and chat history | Structured protocol with context |
| Findings | Spreadsheet and memory | Connected to data and analysis |
| Manuscript | Reassembled at the end | Developed from connected project objects |
Designed for rigorous work
Control, traceability and honest product claims.
SciCollab is built around explicit access, attributable work and portable research outputs. Feature availability is stated plainly; planned capabilities are not presented as live.
- Project-based access
- Attributable changes and versions
- Human review of AI proposals
- Portable research outputs
Questions before you start
SciCollab, in practical terms.
01Is SciCollab an AI writing tool?+
No. It is a research workspace for the full study. AI is a contextual assistant inside selected workflows, not the product's substitute for scientific judgment.
02Does it replace reference managers or statistical software?+
No. SciCollab connects the research logic around specialist tools and keeps evidence, decisions, findings and manuscript work traceable.
03Can I use it for an individual project?+
Yes. The same connected model supports an individual researcher and a multi-role research team.
04Does AI change my research automatically?+
No. Material AI proposals remain reviewable. You decide whether to accept, edit or reject them.
05Can I take my work out of SciCollab?+
Portability is a product principle. Export and readiness capabilities are being released progressively, with their status shown honestly.
SciCollab
Keep the thinking connected from the first question.
Open SciCollab and start your next research project in one traceable workspace.