Proximal generates coding tasks with AI, surpasses $200M in revenue

Proximal, a San Francisco-based AI research lab, has reportedly crossed $200 million in annual revenue by using AI models to generate coding tasks at scale. The company’s approach leans on synthetic data generation and reinforcement learning to build what it describes as high-fidelity environments for training autonomous coding agents. For a company founded in 2025 with roughly 25 employees, that revenue figure would be remarkable. It would place Proximal in rare company among AI startups that have scaled revenue faster than most enterprise software firms in history. What Proximal actually does Proximal builds automated pipelines that generate synthetic code, create evaluation rubrics, run quality checks, and simulate extended software development tasks using multi-agent orchestration. The company released FrontierSWE, a benchmark containing ultra-long-horizon tasks meant to evaluate how well coding agents handle complex, multi-step engineering work. Even leading models like Anthropic’s Claude performed poorly on these extended benchmarks, suggesting that current AI coding tools still have significant ground to cover before they can autonomously handle serious software engineering....