The Engineering Behind Enterprise AI

About – Amit Patriwala

My name is Amit Patriwala, I am a 20+ years Software Development professional and Hands-on Technology Practitioner.

With this simple thought: AI should drive measurable business value, not just demos, I started AI Tech Partner Lab. You can make a prototype of anything in a weekend in most organizations. I’m concerned with the hard part: designing systems that scale, survive real-world load and generate revenue.

My Journey

I began my career as a software engineer and slowly, over time, evolved into architecture: by spending time troubleshooting systems that failed at mid-night; by observing well-done diagrams that failed in production; and by realizing that it is where this gap between a whiteboard and a production system is where most technology investments fail.

In two decades, I have seen the gamut of enterprise software, cloud platforms, SaaS products, and now, all of modern AI engineering. From My work has always been rooted in the code and I have always been fascinated by .NET backends, Azure cloud infrastructure, LLM pipelines, RAG systems, multi-agent orchestration, and voice AI.

That is a hands-on habit on purpose. An architect who can’t build an architect who can’t be trusted.

What I Do Today

My current interests live on the border of AI engineering, cloud architectures, and enterprise software:

  • Building and implementing RAG systems: all the way from basic retrieval to hybrid search, reranking, and RAGAS-evaluated production pipelines. Creating and deploying RAG systems: all the way, from basic retrieval to hybrid search, reranking, and RAGAS-evaluated production pipelines.
  • Creating multi-agent and agentic AI systems, such as voice agents that incorporate real-time STT/TTS pipelines with Deepgram, ElevenLabs, LiveKit and Twilio.
  • Turning enterprise AI platforms into reality: LLM routing, domain specific SLM orchestration, AI governance, and MLOps on Azure.
  • Building AI as a service (SaaS) solutions, including AI solutions in healthcare, sales training, and intelligent automation solutions. Creating AI as a service (SaaS) products, such as AI in the health industry, sales training platforms, and intelligent automation systems.
  • Mentoring technology leaders on how to deploy AI responsibly and profitably at scale

I’m a comfortable technology homebrew, but my technology home is Azure. My AI infrastructure runs across the whole of OpenAI, Anthropic Claude, opensource LLMs – self hosted (vLLM and Ollama) as well as LangChain/LangGraph/LlamaIndex toolchain.

Who I Help

I work with startups developing AI-first products and enterprise teams trying to upgrade their workflows for AI – usually when prototypes need to morph into platforms, or the AI investments begin to pay off.

This blog is for CTOs who are seeking to filter out vendor marketing buzzwords, founders developing something bold on a small team, or engineers encountering production AI for the first time.

Why I Write

I write because I learn by telling. Each article I write, I’m attempting to take something complex, whether it’s a RAG architecture pattern, a multi-agent design trade-off, an Azure deployment challenge, etc., and make it something you can actually do.

I contribute case studies, architecture frameworks, implementation guides, and occasionally a post mortem in all honesty.

No theory without any practical application in it. No hype, no substance.

Beyond the Blog

You can find my work across: