We make enterprise AIless expensive to run.
AI inference software, built by people who have spent their careers on performance, measured and published with its method.
Enterprise AI should be affordable, dependable, and held to the same standard as any other production system a business runs on: the right models on the right hardware, inside infrastructure you control.
Built by people who've been through a technology cycle before.
Between them: nearly twenty years inside Intel's performance and AI infrastructure organization, senior leadership through a major technology acquisition, Fortune 500 AI infrastructure advisory, and published research in GPU-accelerated perception and neural-network design.
A multi-time founder who has lived through several technology cycles firsthand. Sean helped build a technology consultancy in the late 1990s, through the dawn of the modern internet, then founded and built an early e-commerce platform into one of the first true omni-channel solutions before a successful exit to a global software company. He later joined Mailchimp as a member of its senior leadership team, helping guide its rise to one of the most recognized brands and prolific email service providers in the industry, through its 2021 acquisition by Intuit.
Owns everything technical at Score Labs: product, engineering and benchmarks. Before co-founding Score Labs, Ripan spent nearly 20 years at Intel, most recently as a Principal Engineer leading cloud server QoS, end-to-end performance, and AI infrastructure TCO. His career has centered on exactly the problem Score Labs is built to solve, including scaling Intel's own MKL-DNN library. He holds a degree in Electrical Engineering from IIT Kanpur and a master's from Louisiana State University.
Leads Score Labs' kernel and systems architecture work. Ashish holds a PhD in autonomous robotics and neural network architectures from IIT Kanpur, where his research spanned GPU-accelerated perception systems, efficient neural-network design, and low-level hardware/software co-design, published at venues including CVPR, ICRA, and IEEE Robotics and Automation Letters.
Shapes how Score Labs thinks about strategy and global positioning. Sudeep is a Partner and Managing Director at AlixPartners, where he advises Fortune 500 boards and C-suites on AI infrastructure and data center strategy. He holds an engineering degree from IIT Kanpur and an MBA from Emory University, and is a published author, keynote speaker, and media commentator on global trade, disruptive technology, and AI infrastructure.
Every technology wave gets efficient in its second act. AI is entering it now.
We have seen this pattern before: the internet build-out, the first e-commerce platforms, the rise of cloud. The first wave proves the category. The second wave is where the economics get sorted out and adoption becomes broad. AI's first wave has done its job; what has lagged is inference that is efficient, predictable and affordable enough to run at scale on infrastructure a business already knows how to operate.
That is a solvable engineering problem, and it is the one we chose. Score puts each piece of inference work on the hardware that suits it, keeps data where it belongs, and gives the same answer every time. We have spent two years building the pieces; the measured results are on the Results page.
Headquarters
Locations: Atlanta, Portland, Delhi, Bangalore
Benchmark your workload.
We publish the methodology, the baselines, and the range where we lose. Send a workload and we'll test all of it against your reality.