Q-UNIFY runs CBAHI compliance, quality documents, staff files and OVR incidents in one place. The AI reads every document and flags gaps before the surveyor finds them.
0.0
score
Hospital quality score
Survey-ready in 147 days
+2.4 pts vs last month
The demo
Choose your role to explore the prototype.
Upload, validation, version history and expiry tracking for the A to K quality files.
Chapters, standards and measurable elements, each with its evidence and a live compliance score.
Required licences and certifications per job role, with compliance per person and per department.
Reporting form, investigation, root cause, corrective actions with owners and due dates.
Weighted quality scoring across 50 departments and automated periodic reports.
Reads documents, suggests matching standards, detects missing evidence and raises alerts.
On-premises AI
Extracting text
Fire drill report Block C.pdf · 6 pages
Classifying
Quality file H · Facility & safety
Matching CBAHI
FMS.7.2 · 74% relevance
Alert raised
Block D drill missing for 2026
Packaged with Docker for the hospital's servers. Your IT team owns the code from day one.
No. The AI model runs on the hospital's own servers. Documents, scores and incidents stay inside the hospital network.
Always a person. The AI suggests standards with a relevance score, the quality team confirms or rejects every match.
Each department head only sees their own department. Isolation is enforced in the database, and every sensitive action is written to the audit log.
Full source code, database schema, technical documentation, deployment guide and administrator guide, packaged with Docker for the hospital's servers.