MedHive provides a neuro‑symbolic AI knowledge‑management platform for medical device manufacturers that ingests and links all lifecycle data into a secure, domain‑specific knowledge graph. The system enables instant retrieval of internal insights, automatically drafts regulatory artifacts such as 510(k) submissions, and highlights compliance gaps with traceable, hallucination‑scored answers, helping R&D, engineering, quality, and regulatory teams accelerate design decisions and reduce time‑to‑market.
Funding
Funding not disclosed
Founders
Product
Problem
Medical device developers often struggle with fragmented technical, quality, and regulatory information spread across multiple systems, leading to lengthy knowledge retrieval, manual document creation, and increased compliance risk.
Solution
MedHive offers a neuro‑symbolic AI knowledge‑management platform that ingests and connects all data from the device lifecycle into a secure, domain‑specific knowledge graph. The system enables instant retrieval of past insights, automatically generates drafts of technical and regulatory artifacts such as 510(k) submissions, and highlights compliance gaps. By providing traceable, AI‑augmented answers with hallucination scoring, MedHive reduces manual research, accelerates design decisions, and shortens time‑to‑market while maintaining data sovereignty within the customer’s environment.
Target Audience
Primary customers are medical device manufacturers and their R&D, engineering, quality, and regulatory affairs teams seeking faster, more reliable knowledge access and automated documentation.
Features
- Automated ingestion of diverse sources (design files, requirements, protocols, reports, patents, field data, regulatory documents) into a unified knowledge graph
- Neuro‑symbolic AI engine that answers queries using only verified internal content and supplies traceability links to source documents
- Draft generation for technical and regulatory deliverables (e.g., 510(k) submissions) with alignment to regulatory structures
- Compliance gap analysis that compares content against quality and regulatory expectations and provides actionable recommendations
- Secure, isolated cloud deployment with AES‑256 encryption at rest, TLS 1.2+ in transit, MFA, RBAC, and scoped API keys
- Integration connectors for common QMS, PLM, document repositories, cloud storage, and custom APIs
- Hallucination scoring to flag potentially unsupported AI responses and ensure content validity