Speaker Profile

CEO, Tunld

Biography
Clynt Taylor is co-founder and CEO of Tunld, Inc., a new AI-powered precision oncology informatics platform. He has been an innovator in healthcare for over 35 years, as an entrepreneur and senior executive with startup and growing companies. Most recently he served as CEO of Trapelo Health, Inc., an oncology decision support company later acquired by NeoGenomics in 2021. He assumed the role of NeoGenomics Informatics Division president until 2023 when he left to launch Tunld, Inc. Since beginning his career at IBM, hes held various leadership roles at healthcare technology companies including NextGen, HealthVision and at Galvanon Healthcare Solutions as Co-founder and CEO (purchased by NCR). He also held senior executive roles with Eviti, Inc. and with NantHealth, including as Sr. VP of Marketing leading the launch and commercialization of GPS Cancer, a first-of-its-kind, comprehensive test that integrates whole genome (DNA) sequencing, whole transcriptome (RNA) sequencing, and quantitative proteomics.


Talk
Bringing Your Data to Life
Your healthcare data can be messy, inconsistent, illegible, even incoherent. But its gold if you can mine it, something exceedingly hard to do at scale. Tunld brings your data to life. Ingesting thousands of documents in all formats, Tunld identifies, parses, normalizes and contextualizes into discrete forms giving you a powerful new data asset.


AI and Data Sciences Showcase:
Tunld

Tunld uses a symphony of multiple technologies to transform static documents into valuable clinical discrete data - at scale.

 Session Abstract – PMWC 2025 Silicon Valley

Showcase Track S1 - February 5 9.00 A.M.-3.45 P.M.,Showcase Track S1 - February 6 9.45 A.M.-4.00 P.M.,Showcase Track S1 - February 7 11.15 A.M.-2.00 P.M.


The PMWC 2025 AI Company Showcase will provide a 15-30 minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.

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