MRI Reading & AI Recommendations
Possible findings flagged for radiologist review.
View case
Medical Research Workspace
From literature search to manuscript, with review built in.
The challenge
Clinical research teams juggle literature searches, PDFs, screening decisions, extraction spreadsheets and manuscript drafts across different tools, with reviews tracked over email.
What we built
A research workspace that carries a study from literature search to manuscript: publication uploads, study screening, structured data extraction, review approvals and manuscript editing. It adds multilingual dictation, research exports and limited local medical image previews.
The AI layer
- A local AI connector proposes extraction, analysis and manuscript contributions.
- Researchers review and approve every AI contribution before it is used.
How it works
The workflow, step by step.
- 01Search the literature
- 02Screen studies
- 03Extract study data
- 04Review and approve
- 05Draft the manuscript
Architecture
How the pieces connect.
Inputs
- Publications & PDFs
- Screening decisions
- Extracted study data
- Dictation
The system
- Literature search
- Study screening
- Structured extraction
- Review approvals
- Manuscript editing
- Dictation & exports
AI
- A local AI connector proposes extraction
- Researchers review and approve every AI contribution before it is used
People
- Researcher
- Reviewer
- Principal investigator
Outputs
- Structured datasets
- Research exports
- Manuscript drafts
Functional architecture. Integrations and hosting are tailored to each client's environment.
Modules
Everything in one system.
01Literature search
Search and collect publications in one place.
02Study screening
Screen studies with recorded decisions.
03Structured extraction
Capture study data in a consistent structure.
04Review approvals
Reviewer sign-off built into the workflow.
05Manuscript editing
Draft the manuscript alongside the evidence.
06Dictation & exports
Multilingual dictation and research exports.
Interface preview
What your team would see.
Illustrative interface · sample data
Who uses it
Built around real roles.
Researcher
Searches, screens and extracts.
Reviewer
Approves screening and extraction.
Principal investigator
Oversees the study and the manuscript.
A team reviewing four hundred papers screens them in the workspace, extracts outcomes into a structured table with AI suggestions they approve one by one, and exports the dataset straight into the manuscript draft.
Build your version
Start here, extend further.
Capabilities we can build on this foundation for your version of the system.
- PRISMA-style flow diagrams generated from screening decisions
- Duplicate detection across imported references
- Reviewer disagreement resolution workflow
- Citation formatting for target journals
- Meta-analysis tables built from extracted data
Questions
What clients ask us.
Does study data leave our environment?
The AI connector runs locally, so extraction and analysis can happen without sending data to an outside service.
Can the AI write the paper?
No. It proposes extraction, analysis and contributions, and researchers review and approve everything.
Can you build a version of this for our business?
Yes. Every system starts with a discovery conversation about your workflow, data and goals, and we adapt the design to fit. Most engagements produce a working, testable system within a few weeks to a couple of months, depending on scope.
Can it integrate with the systems we already use?
Integration with existing tools such as ERPs, accounting packages, databases and document stores is scoped during discovery, so the system fits around how you already work.
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