About Alchymos
Building the infrastructure behind dependable AI agents.
As AI moves from experiments to everyday workflows, teams need a clearer way to manage performance, cost, and reliability. That is the problem we are working on.
Our perspective
More capability needs better foundations.
Agent systems call models, tools, and data sources repeatedly. As those systems grow, the work behind each response becomes harder to understand and more expensive to run.
Alchymos is building an agent-aware layer for caching and visibility. The goal is to help engineering teams see what is happening, reuse useful work, and make thoughtful decisions about speed, cost, and control.
We began with a practical question: what should infrastructure understand about an agent workflow that a conventional cache cannot?
What guides the work
Start with the workload
Design around the real shape of agent requests, rather than asking teams to change everything to fit the infrastructure.
Make tradeoffs visible
Performance, cost, and safety decisions are easier when teams can see the behavior behind them.
Earn trust in production
A useful platform should be understandable, adaptable, and dependable as requirements change.
Founder
Built by Carlos Rufo
Carlos founded Alchymos after years of building developer tools, APIs, and software infrastructure. His work on agent systems brought a recurring problem into focus: teams need to move quickly without losing control of latency, cost, and reliability.
Alchymos brings that experience to a focused infrastructure product for teams building with AI.
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