Authors : Kapil Kumar Goyal

Volume/Issue : Volume 10 - 2025, Issue 5 - May

Google Scholar : https://tinyurl.com/mvdsfjsk

DOI : https://doi.org/10.38124/ijisrt/25may1641

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The journey of AI models from a proof of concept to a full AI/ML operational system is often hampered by a lack of resources, specialized infrastructure, and just insufficient cross-functional coordination. We present a framework called "Zero-to-Live" for these under-resourced teams to guide them to AI operational success with the least overhead possible. The way we work is grounded in lean product thinking, using a generalized modular architecture, and good old frugality. We share what are, to our minds and experiences, the key ingredients to success. And we most definitely do not share with you what not to do. We also give some real-life examples of how we ourselves have succeeded in deploying AI systems to production in tech startups and mid-sized enterprises.

Keywords : AI Productization, Lean MLOps, Model Deployment, Resource-Constrained Teams, Lightweight Architecture, Agile AI, Data-Driven Delivery.

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