Project Overview
A healthcare organization partnered with Cubet to streamline triage operations using document-based AI assistance. The initiative aimed to support clinicians by improving how they process diverse clinical records such as scans, lab results, and referral documents. The focus was on helping healthcare professionals gather insights from fragmented information without altering their current tools or decision-making authority.
Industry
Healthcare
Challenges Addressed
- Patient data arrived in mixed formats with minimal structure
- Manual effort was required to compare and interpret reports from various sources
- Existing tools lacked contextual understanding across multiple documents
- Clinicians relied solely on experience to prioritise patient cases
- Technical constraints demanded on-premise operation and strict regulatory compliance
- Goal was to assist, not automate, clinical judgement
Collaboration in Action
Cubet introduced a triage support platform leveraging its AI system, Whizz, built specifically for handling healthcare documentation. Doctors uploaded case-related files into a secure environment where AI modules parsed, examined, and summarised key elements. These outputs were returned as helpful overviews—while clinicians retained full control over review and decisions.
Technologies Deployed
- Whizz AI platform tailored for healthcare document workflows
- Multi-format file handling and harmonisation engine
- Clinical context-aware AI modules
- Independent reasoning across multiple inputs
- Explanation-based summaries referencing original inputs
- Localised deployment architecture
- Built-in access control and compliance support
Innovative Features
- Designed for real-world medical documents
- Combines inputs from labs, scans, and notes into one clinical view
- Flags relationships and gaps across multiple files
- Offers summarised support with links to original data
- Suggests possible directions—not conclusions—for clinician consideration
- Modular design for clarity, control, and traceability
Value Delivered
For Medical Teams:
- Easier navigation through case data
- Quicker pattern recognition
- Assistance in identifying key indicators early
- Reduced fatigue when handling high patient volume
For Support Staff:
- Smoother triage flow
- Consistent case handling standards
- Boost in case throughput during peak hours
For Administrators:
- Clear boundaries between automation and decision-making
- Greater trust from clinical staff in AI-backed tools
- Readiness for broader AI use across departments
User Feedback
Clinicians appreciated the design, which maintained transparency and choice. The ability to trace insights directly to their sources gave confidence, while the assistive—not intrusive—nature of the tool helped it gain fast acceptance.
Conclusion
The project proved that AI can play a supportive role in medical triage without altering human responsibility. By providing consistent, explainable analysis of patient records, Cubet’s solution helped clinicians save time, focus better, and handle growing workloads more effectively—setting the stage for continued innovation in document-centric healthcare systems.