AI Infra for real-time vision applications
Overshoot makes it easy for developers to build and run real-time vision applications. AI can see and understand the physical world. This unlocks new applications in physical security, safety, gaming, robotics and general consumer products. Soon, video agents will watch your home and your pet when you’re away. However, existing platforms make it painful for developers to build these real-time applications. Slow inference. Limited model availability. Break at scale. Overshoot solves this. Today, 300+ developers connect live video feeds to the largest collection of Vision Language Models with 3 lines of code. And get responses in less than 200ms. 10x faster than any existing inference platform. Zero infra headache. Our moat is focus. Image and Video are fundamentally different modalities from text. By focusing on them, we are able to make strong technical leaps from codec, streaming protocols to inference engines. Younes and Zakaria are cousins. Zakaria graduated top of his class at LSE and MIT, and later built low-latency high-throughput pricing systems (surge) at Uber and inference engines at Meta. He previously built and sold a software product and won several prominent AI hackathons. Younes was a founding engineer at Cosmonio (later acquired by Intel). He built a training and serving Computer Vision platform from scratch. He witnessed firsthand customers abandoning traditional Computer Vision because it lacked the “general” intelligence LLMs have today. Together we’ve shipped large-scale systems and know where they break.
Founder
Ex-Intel Computer Vision AI Frameworks Engineer. CTO of Overshoot. Building the platform for realtime vision powered by LLMs.
Founder
Co-founder and CEO of Overshoot. Prior to this, Zakaria spent 7 years building pricing algorithms at Uber and writing GPU kernels at Meta AI. Won 3 prominent AI hackathons. Built and sold a software product while in grad school at MIT. He graduated top of his class at the London School of Economics. Likes to nerd out on anything inference and VLM / video understanding.
