Using cloud and AI well is a cloud architect’s job. Mof starts with cost — unify your clouds, see it, cut it — then adds AI for the architect’s judgment. That’s MOFIS.
We first set out to build DevOps tooling, but the space was already crowded. Turning to FinOps, our cloud-architect experience made one thing clear: for users, cost is almost always first — many teams will even switch cloud providers to save money.
Yet optimizing and managing cloud cost is hard to start, and an architect who doesn’t know your business can’t give the right plan. So the customer has to make the call — what they need is trustworthy data and a tool that fits their hand, not a pile of unreadable bills. That’s where Mof started.
We’ve spent the most effort on data collection and cleaning and a clear product experience. As for right-sizing advice, machine recommendations never won customers over — the machine doesn’t know their business. But the AI era changed that: we supply the data and skills, and let AI produce the plan. That’s MOFIS (AI cloud architect).
Former AWS engineer and senior solutions architect at Tencent Cloud, delivering hundreds of cloud solutions to 100+ enterprises (Apple, Xiaohongshu, OPPO and more), and led a cost-optimization platform that lifted team efficiency 3× and cut cost 30%+. Author of the rk-boot microservice framework. BEng in Software Engineering (Dalian University of Technology), MS in Computer Science (Illinois Institute of Technology, USA).
Former engineer at Amazon (USA) on a financial big-data platform processing 1B+ records daily; previously Baidu wealth-management platform and senior engineer at Tencent Cloud, where he owned a Tencent Cloud sub-module of the open-source deployment platform Spinnaker. BEng in Software Engineering (Dalian University of Technology), CS graduate study at the University of Pittsburgh (USA).


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