Delphina is an AI Data Scientist platform designed to help data science teams accelerate their machine learning impact. Delphina provides software solutions that automate and streamline various data science workflows, enabling teams to build, deploy, and manage machine learning models more efficiently.
Delphina's core offering centers on augmenting data science teams with artificial intelligence to reduce bottlenecks and speed up experimentation, model iteration, and deployment. By leveraging AI-driven tools, Delphina aims to make advanced data science capabilities accessible and productive for organizations seeking to drive value from machine learning initiatives.
How was Delphina started?
Delphina was founded in San Francisco by a team of industry veterans and technical leaders from top technology companies and academic institutions. The founding team includes:
- Jeremy Hermann (Head of ML Platform at Uber, architect of Michelangelo, co-founder of Tecton)
- Duncan Gilchrist (Director of Data Science at Uber, VP Data Science & Engineering at Gopuff, PhD Harvard)
- Thomas Barthelemy (Staff Engineer at Coursera, early team through IPO, Stanford)
- Pedro Olea (Head of Rider Pricing Science at Uber, Delivery Science at Gopuff, PhD Princeton)
- Wei Hao (Machine learning at Google, Facebook, Sisu, PhD Princeton)
- Eric Qian (Software Engineer at Scale AI, Facebook, MIT)
- Sara Gates (Content Advisor at Monte Carlo, Mailchimp, Vacasa)
- Wenbo Wang (Product Designer at Databricks, Cloudera)
- Priscilla Choi (Operations at Nuro, Salesforce)
- Jason Xu (SWE at Scale AI, TruckSmarter, UCLA, Berkeley MEng)
- Jack Zhao (SWE at Meta, Grail, Betteromics, Waterloo)
- Hugo Bowne-Anderson (Community Advisor at Outerbounds, DataCamp, Yale, PhD UNSW)
This diverse group brings together expertise in machine learning, data science, engineering, and product design, with experience at leading organizations across the tech ecosystem. You can read more about their story and team on their About page.
Who uses Delphina?
While specific customer names have not been publicly disclosed, Delphina is designed for data science and machine learning teams within organizations looking to enhance the efficiency and impact of their ML projects. Typical users are likely to be:
- Data scientists and ML engineers at mid-sized to large technology companies
- Analytics teams seeking to automate manual processes
- Organizations pursuing scalable machine learning operations (MLOps)
What makes Delphina different?
Delphina differentiates itself by focusing on automating the expertise of a data scientist using AI, streamlining complex workflows, and helping teams iterate faster on machine learning solutions. The company leverages the deep practical experience of its founding team, who have built and scaled ML platforms at companies like Uber, Gopuff, Coursera, Google, Facebook, and others.
Where is Delphina based and how big is the company?
Delphina is headquartered in San Francisco, United States. As a privately held company, it has a team size of 11-50 employees, reflecting its early-stage focus on innovation and rapid product development.
Learn more
To get the latest updates, join the waitlist, or explore job opportunities, visit delphina.ai.
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