Validate clinical programmes, patient flow, lab adjacencies, and infrastructure demands — before design decisions lock in decades of operational performance.
errors caught at feasibility, not after BIM
infection control zone conflicts in generated layouts
of operational performance determined by early planning
AI-Powered Planning
Medical Centres · Hospitals
Trusted By Teams Delivering Complex Projects.
The Problem
Hospital design errors are not just costly to fix — they affect clinical outcomes, staff efficiency, and patient safety for the operational life of the building. Research laboratory adjacency failures compromise scientific quality for decades.
— How It Works
Define
Define clinical programme: departments, bed counts, procedure volumes, acuity mix
Import
Import site data and building envelope constraints
Generate
Generate multiple hospital layout scenarios with AI planning tools
Validate
Validate departmental adjacencies, patient flow, and circulation efficiency
Test
Test infection control zoning and regulatory compliance
Export
Export validated programme layouts to BIM for detailed clinical design
Platform Capabilities
Use Cases
Healthcare trusts and authorities planning new hospital facilities
Universities planning research and science facilities
Private healthcare operators designing specialist clinical facilities
Life science developers building research campus facilities
errors caught at feasibility, not after BIM
infection control zone conflicts in generated layouts
of operational performance determined by early planning
Future Vision
As healthcare systems face growing demand, ageing infrastructure, and increasing clinical complexity, hospital planning must become faster and more data-driven. DBF enables teams to navigate this complexity by validating more options, earlier, with greater clinical confidence than traditional workflows allow.