SCI · Medical Research
Sci Vault: research imaging
archived and findable,
ready for cohort screening and multi-center research
An imaging archive and data management platform for medical research:
- Structured archiving of research imaging
- Unified case data management
- Case-linked retrieval and collaborative sharing
Bring the research imaging scattered across imaging devices, department workstations and personal computers into one system: retrieve images by case, share with partners within defined permissions, and have the complete dataset assembled in one pass at study close-out and reporting.
Tell us your research scenario and compliance requirements when booking · On-premises deployment · Tiered permissions
Research Data Pipeline
LiveArchiveARCHIVE
Structured image archiving · Unified case management
RetrieveRETRIEVE
Case-linked retrieval · Research cohort screening
ShareSHARE
Tiered permissions · Multi-center collaboration
zhiwo-sci> filter a case cohort by enrollment criteria
Visibility of search results and linked images follows account permissions
Structured Archiving
All imaging in one repository
Case-Linked Retrieval
Cases and images connected
Tiered Permissions
Multi-center collaboration
On-Premises Deployment
Data can stay in your server room
Pain Points
Incomplete datasets, manual screening,collaboration without clear boundaries
These situations recur in research departments — and each one can be checked against the live system, item by item, in a demo.
At study close-out, the data isn’t all there
Images sit on imaging devices, department workstations and personal computers with no structured archive, so provenance and versions are hard to trace. Assembling one complete dataset for close-out or a results report means searching every machine.
Cohort screening runs on manual record checks
Imaging and case information are kept apart, so screening a research cohort means flipping through records and comparing spreadsheets by hand. As sample size grows, the screening cycle stretches out — and cases get missed.
Multi-center boundaries are hard to draw
In multi-center research, each center’s data permissions and sharing boundaries are difficult to pin down; the materials required for ethics and compliance review are hard to assemble side by side, so collaboration stalls in rounds of back-and-forth confirmation.
Features
Six capabilities, from archive to collaboration
Every one of them runs live at sci.zhiwoai.com — in a demo we can open them one by one for comparison.
Structured Image Archiving
Scattered research imaging goes into one repository, managed in structured form and linked by case.
Full-Lifecycle Imaging Management
From intake and archiving to long-term retention, imaging and case data are managed in one system and available at any time.
Case-Linked Image Retrieval
Cases and images are linked, supporting retrieval of images by case.
Research Cohort Screening Support
The case-linked imaging data supports screening for research cohorts.
Tiered Permissions
Data access is divided by role and level: who can view which images is decided by account role.
Collaborative Sharing (Multi-Center)
Open cases and images to research partners within permission boundaries, supporting data collaboration in multi-center studies.
Scope
What this systemmanages — and what it doesn’t
What we do, what we don’t, and how to buy — written out first, so cooperation stays simple.
What we do
Research imaging data management at single-hospital and department level: structured archiving, case-linked retrieval, tiered permissions, and collaboration for multi-center studies.
What we don’t do
Sci Vault is positioned as a research imaging data management tool; it does not perform AI lesion diagnosis. Regulatory filing for diagnostic products is outside the system’s scope, and the compliance boundary involved is aligned at the proposal stage.
How to buy
Sold as a finished product, deployable on-premises in the institution’s own server room, with workflows tailored as needed. See the system first and verify each capability in a demo, then move into the hospital procurement process.
Zhiwo Engine
Runs on the L1 Multimodal Analytics layer of Zhiwo Engine
The engine has three layers: L0 Sensing & Access handles device connectivity and L2 Operations & Maintenance handles device upkeep — this system mainly uses L1, where archiving, retrieval and analytics all happen.
Multimodal Big Data Analytics Platform
Structured data and imaging are organized and analyzed on a single platform: one natural-language sentence generates queries and visual dashboards, and archiving, retrieval and cohort screening are all served from this layer.
The multimodal analytics layer supplies archiving, retrieval and visual-understanding capabilities together; when the platform’s capabilities upgrade, every product line benefits. Explore the full engine
FAQ
Common questions on permissions, ethics and procurement
Multi-center studies, on-premises deployment, and how the system connects with the hospital’s PACS.
Q1What problem does Sci Vault mainly solve?
It structurally archives the research imaging scattered across devices and individuals, manages it linked with case data, supports retrieving images by case and screening research cohorts, and enables collaboration and sharing under tiered permissions.
Q2Can the system support multi-center studies?
The system is designed around tiered permissions and collaborative sharing, and supports multi-center research.
For the materials that ethics review and compliance require, we list and provide them per project requirements at the proposal stage.
The tiered permissions and data-management design can be checked item by item in a demo, against your review requirements.
Q3Can the imaging data stay in our own server room?
Yes. The system supports on-premises deployment, so data can stay entirely in the institution’s own server room.
Q4Can it connect with the hospital’s PACS?
The system is positioned as research imaging data management and does not replace the clinical image-transfer role of a PACS.
Feeding data in from the hospital PACS (exported files or interfaces) depends on the hospital’s interface conditions and approval process; the exact scope of DICOM and HL7 support is confirmed item by item during demos and proposal — no certification claims are made here.
Contact Us
Turn your review requirements into a checklist,and we’ll verify each item in the demo
Research direction, imaging data volume, ethics and on-premises requirements — state these in your email and the demo will be prepared around them. Permission tiers and data management design can be walked through line by line against your review materials.
Product Lines
Zhiwo EduCare (LMS)
Learning management system (LMS) · Enrollment approval · Assessment & certification · Certificate verification
Zhiwo UAV Cloud
Equipment Operations Cloud · Fleet onboarding · Mission scheduling · Flight data archiving
Zhiwo WMS
Warehouse management system (WMS) · Multi-warehouse, multi-owner · Barcode & RFID · Overseas warehouses
All four product lines
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