Callosum

The explosion in AI inference workloads across enterprise and scientific computing has put a new premium on cost efficiency, especially as single-turn chatbot inter­ac­tions give way to long-running agentic operations executed behind the scenes. Callosum recognizes that the infra­struc­ture for AI computing is increas­ingly hetero­ge­neous, and that workloads don’t always need to be routed to the most expensive models and chips. The company builds algorithms that can decompose token-intensive workloads and assign them to the models and silicon that offer the most efficiency for a given task on a given schedule. As the company says: ​“The problems worth solving are inherently hetero­ge­neous, and so the intel­li­gence we build to solve them must be too.”