One design change ripples across requirements, risk files, DHF/DMR, labeling, test protocols and suppliers — and teams lose weeks tracing it by hand. MedHive maps the full impact of a change across your systems. Built with medical-device R&D, quality and regulatory leaders.
Cross-system change impact for sustaining engineering
MedHive builds a knowledge graph of your product documentation, so a proposed change can be traced to every artifact it touches — before the change package is opened. Instead of hand-searching six systems, your team sees the full blast radius of a change in one view, with traceability back to the source documents.
One change — every affected artifact, traced in one view.
Welcome to MEDHIVE
MedHive is an AI-based Knowledge Management Platform specifically developed for the medical device industry to transform the R&D processes, eliminate data barriers, and open a quicker, more efficient pathway from concept to market.
What we measure with every design partner
Change-package preparation time, baselined with your team in week one and tracked through the pilot.
Baselined together at kickoff — results shared only with partner approval
Systems traced per change — requirements, risk files, DHF/DMR, labeling and test protocols.
Baselined together at kickoff — results shared only with partner approval
Duration and success criteria agreed together before kickoff — no open-ended engagements.
Baselined together at kickoff — results shared only with partner approval
How MEDHIVE Works
MedHive unifies fragmented knowledge, automates repetitive tasks, and empowers your cross-functional teams with the insights needed to accelerate innovation and improve decision-making — designed to shorten time-to-market, and we will measure it with you.
Accelerated Medical Device R&D
MedHive unifies fragmented knowledge, automates repetitive tasks, and empowers your cross-functional teams to accelerate innovation.
learn moreRegulatory Document Creation
Proactively generates regulatory drafts and automates compliance documentation to keep submissions on schedule.
learn moreKnowledge Collaboration Hub
A single intelligent knowledge graph that connects Product, Quality, Operations, and Finance teams.
learn moreMaking a Big Impact on People's Lives
By reducing the time spent tracing changes and assembling documentation, MedHive is designed to help life-saving medical devices—from advanced implants to vital diagnostic tools—move from concept to patient bedside sooner.
MedHive is designed to help medical device manufacturers improve product reliability and documentation quality, supporting better patient outcomes. We will measure these outcomes together with each design partner.
learn moreAdvanced Implants
From concept to patient bedside faster than ever before.
Vital Diagnostics
Superior product reliability and fewer recalls.
Enhanced Outcomes
Directly improving health outcomes and quality of life.
Next-Gen Pacemakers
Reaching patients years sooner.
Committed to Security
MedHive's AI architecture is designed to follow the major data privacy and security regulations (including HIPAA and GDPR principles), offering options for secure cloud deployment and stringent Role-Based Access Controls (RBAC) to protect your intellectual property and sensitive data.
- Data encrypted in transit (TLS 1.2+) and at rest
- Role-based access control (RBAC) and least-privilege access
- Continuous monitoring, logging and alerting
- SOC 2 Type I audit planned — timeline available on request; controls designed to ISO 27001
Why MEDHIVE?
MedHive significantly enhances core QMS/PLM capabilities by providing a Unified Knowledge View across all vital business domains—Product, Quality, Operations, and Finance. With a powerful Neuro-Symbolic AI approach, leveraging both historical and current knowledge to generate concrete outputs, MedHive streamlines development and compliance.
| Feature | MedHive | LLMs (chat, API) | Ketryx | Collate | Siemens Teamcenter | PTC Windchill | Greenlight Guru | Qualio |
|---|---|---|---|---|---|---|---|---|
| Content & traceability MindMap | ||||||||
| Domain / context-targeted AI | ||||||||
| Historical knowledge reuse | ||||||||
| Per-artifact accuracy score (RF) | ||||||||
| Automated artifact generation | ||||||||
| Automated change management | ||||||||
| Gaps identification | ||||||||
| Cost | Low | Low | High | High | High | High | High | High |
An AI-first approach that leverages historical information plus domain- and workflow-specific context — with per-artifact RF scoring to catch inaccurate AI-generated knowledge.
Suite agents draft only inside their own system of record — an agent cannot walk a dependency graph it doesn't have.
Bring us a real change scenario
Tell us about a change your team recently traced by hand — we'll show you what MedHive would have surfaced, and we will measure the difference with you.
Designed to cut change-package and documentation time
We will measure it with you — join the design-partner programme.