Enlil Expands AI-Powered Traceability Platform in MedTech
Enlil, Inc. has announced growing momentum for its AI-powered development traceability platform across the global MedTech ecosystem, as stated in a press release. Since appointing Nader Fathi as CEO in February, the company has expanded its reach among OEMs, contract manufacturers, and industry partners, now boasting over 600 users worldwide.
The platform integrates AI-powered intelligence, including a private large language model-driven chatbot named Ask Lily, which provides rapid insights to engineering, quality, and regulatory teams. This allows for smarter decision-making without compromising sensitive intellectual property or compliance integrity.
Enlil's platform is designed to overcome challenges associated with fragmented technology stacks and siloed documentation, offering end-to-end traceability and secure cross-functional collaboration. It integrates key product development disciplines such as Requirements Management, QMS, PLM, Manufacturing, ERP, Regulatory Compliance, and Post-Market Surveillance into a unified digital thread.
Shifamed, the innovation network backing Enlil, supports the platform's expansion with advanced AI capabilities, establishing it as a leading solution for regulated product development in the MedTech sector.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Life AI Weekly or Daily AI Brief.
Also, consider following us on social media:
More from Life Sciences
Oct 16 Manhattan Physician Invests in RunPractice Oct 16 Attilio appoints Buck Institute CEO Eric Verdin as cochairman Oct 16 Aignostics launches HETA Clinical for pathology workflows Oct 16 Specialty1 Partners Invests in AI for Dental Practice Operations Oct 15 Study Tracks 270 Million Clinical AI Queries on OpenEvidenceLife AI Weekly
Weekly coverage of AI applications in healthcare, drug development, biotechnology research, and genomics breakthroughs.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Elisity Joins Open Secure AI Alliance
Illumina Launches BioInsight Platform for Genomic Research
Emplifi Adds AI Workflows and Analytics to Customer Experience Platform
NewMed Energy deploys GeoIntelX AI for gas projects
Enveda Raises $311 Million for AI Drug Discovery
Daily AI Brief: the AI news that matters, in your inbox.