Most organizations are learning tools. Decyra focuses on designing systems that improve decisions, scale intelligence, and create real business outcomes.
We don’t position AI as a set of tools or platforms. We approach it as a system design problem.
Every engagement starts with identifying where decisions break down, how data flows, and where intelligence can be embedded into workflows. From there, we design architectures that connect data, AI models, and human oversight into a scalable system.
This is what enables organizations to move from experimentation to production-grade AI systems.
Decyra works with startups and enterprises that are building or scaling data platforms, analytics systems, and AI initiatives— but need clarity on what to build, what matters, and how to scale it.
Mukund Kumar Mishra Principal Architect – Data Platforms & AI Systems
Mukund brings 20+ years of experience designing and modernizing enterprise-scale data platforms across banking, payments, manufacturing, and government sectors.
His work spans Snowflake, Microsoft Fabric (OneLake), Azure and AWS—building large-scale, governed data platforms supporting analytics, regulatory workloads, and AI systems.
More recently, his focus has been on AI-native architectures, including Retrieval-Augmented Generation (RAG), multi-agent systems, and integrating LLMs into enterprise data platforms.
Most firms help implement tools. Decyra helps define what should be built in the first place— and how to design it for long-term scale.
The focus is not just on architecture diagrams, but on building systems that continuously improve decisions, adapt with AI, and deliver measurable outcomes.