Medical imaging
Compute evaluation for reconstruction, enhancement, segmentation and device-side workflows.
HOLYCORESMEDICAL DEVICE PARTNERS
With intelligent compute, medical devices
become more trustworthy.
We work with device manufacturers, algorithm teams, research institutions and clinical engineering partners on verifiable, maintainable systems with explicit boundaries.Discuss a use case →
COLLABORATION AREAS
From device compute to controlled workflows.
HOLYCORES provides a general compute and software foundation. Intended use, classification, clinical evaluation and market authorization are defined per project and target jurisdiction.Diagnostics and laboratory
Vision, signal and multimodal processing with local control and analysis.
Surgical and robotic systems
Joint engineering for low-latency perception, navigation, control boundaries and redundancy.
Monitoring and wearables
Edge intelligence under power, privacy, connectivity and continuous-operation constraints.
These are examples of technical collaboration. They do not indicate that any HOLYCORES product has medical-device clearance, certification or authorization, and they are not medical advice.
PLATFORM CAPABILITIES
A complete device boundary, not just a model.
Compute, software, data, security, thermal design and lifecycle management must work as one system and be validated for the target device and intended use.Heterogeneous compute
- Vision, signals and inference
- Deterministic tasks and isolation
- Power- and thermal-aware optimization
Controlled software stack
- Model conversion and versioning
- Runtime, operators and profiling
- Reproducible build and deployment
Security and data boundaries
- Identity, access and updates
- Local processing and minimal exposure
- Component inventory and response
Long-term maintenance
- Compatibility and change control
- Traceability and field feedback
- Supply-lifecycle planning
EVIDENCE BEFORE CLAIMS
Build the evidence before defining the claim.
Joint validation begins with intended use, users, environment and hazards, translating model metrics into device-level success criteria with explicit versions, datasets, conditions and limitations.
- Use and riskUsers, workflow, abnormal states and controls
- Data and modelProvenance, representation, bias, version and evaluation
- System validationPerformance, latency, power, stability, security and interoperability
- Change controlImpact of model, software, component and manufacturing changes
RESPONSIBILITY MODEL
Clearer boundaries create stronger trust.
Roles, deliverables, data, IP, quality activities and regulatory responsibilities must be defined in writing for each project.Compute platform, software interfaces, technical information, known limitations and agreed engineering support.
Intended use, design controls, risk management, product validation, submissions, manufacturing and post-market duties.
Data governance, model development, performance evidence, bias assessment, versions and integration.
Needs research, workflow evaluation and evidence generation under applicable ethics and data rules.
COLLABORATION PATH
From problem definition to controlled development.
Progress depends on joint technical, quality, regulatory and commercial feasibility.Discover
Define use, device, users, environment and baseline.
Prove feasibility
Non-clinical engineering prototype for compute, software, data and interfaces.
Develop jointly
Align design inputs, risk controls, verification and change processes.
Support productization
Integration, lifecycle and issue response for the agreed platform.
MEDICAL DEVICE COLLABORATION