Applied Compute builds custom AI models trained on enterprise proprietary knowledge to deploy agent workforces at scale. The company provides Specific Intelligence - custom models paired with proprietary agents and in-house training infrastructure - enabling Fortune 50 companies to validate and deploy solutions in days rather than months.
The company's technical foundation spans reinforcement learning, post-training, and ML systems infrastructure purpose-built for agent deployment. Applied Compute embeds engineers directly within client organisations and develops its entire stack in-house, prioritising rapid iteration and continuous improvement. Clients include DoorDash, Cognition, and Mercor, with deployments across logistics, software, and enterprise sectors.
Applied Compute has secured $80 million in funding from Benchmark, Sequoia, and Lux Capital. The founding team comprises former founders, top AI researchers, and International Math Olympiad winners, reflecting technical depth across reinforcement learning and agentic systems.
