When your product needs a high performing algorithm, powerful computer vision, or intelligent machine-learning AI, we can help develop or improve your offering.
Bloom is revolutionizing health tech with daily urinalysis to track your 15+ important medical bio-markers: Ketones, Vitamin-C, Hydration, etc.
The Bloom computer vision algorithm wasn’t performing where the team needed to reach their next inflection point, raise follow-on funding, and launch to the masses. Our team worked with them to dramatically improve their technology, add additional functionality, and get to the next level.
improvement to existing algorithm
5k+ pre-orders of 40k+ products. Raised multiple rounds of venture capital.
Best Apps is a custom apparel platform, where fans can partner with their biggest stars - whether celebrities, brands or athletes - to create custom clothing.
Best Apps needed our help developing a moderation system to monitor and approve images and custom text being added by fans. Uploading your own image next to famous Mohammed Ali was a huge innovation, and they needed our help to execute it. Our team developed their entire machine learning moderation strategy and built it scalably.
moderation accuracy (4% elevated to human review)
Major launch with A-list celebrity. 4m visits in 3 days over $1m in revenue. Raised large Series A.
Streamoid is a fashion-tech company who’s super-intelligent fashion AI acts as a highly trained stylists and shop-assistants while providing the largest fashion retailers with an in-depth knowledge of their product catalogue.
Streamoid needed help training their machine learning models, including building the models from scratch and sourcing training data. Our team built the scraping engine to source and label training data and then trained a recursive neural network to power Streamoid’s AI.
garment classifier across 100+ categories
Partnership with Target Raised multiple rounds of venture capital
Our data scientists - from places like Stanford, CalTech and MIT - are highly collaborative, efficient and pragmatic.
Data scientist with more than 20 years of experience using statistics and machine learning to analyze datasets in physics, finance, and online petitions. B. Magna Cum Laude in Chemistry & Physics from Harvard College and PhD from Cal Tech in Experimental High Energy Particle Physics.
Data scientist with experience building ML-based data mining solutions, with prior work in a variety of fields, including financial modeling, energy policy, and cybersecurity. Strong cross-functional background in signal processing, software development, and applied statistics. Dual degree in Statistics and Computer Science from UC Berkeley.
Senior data scientist with a passion for developing creative solutions to complex problems. Over the past 7+ years, he has demonstrated this by utilizing supercomputers to solve partial differential equations during his PhD at Princeton, as well as spearheading the integration of machine learning into a health-tech startup, starting from the ground up and reaching millions of users.