From the Architecture Desk
Technical writing on agentic AI architecture, production ML systems, and the engineering decisions that separate pilots from deployed systems.
Every post here comes from a system I have built or am designing — each says which — and links to the matching case studyso you can see the architecture behind the advice. Qualifying inbound leads with AI, multi-agent systems for business intelligence, monitoring AI quality in production and connecting agents to company tools safely: pick the problem closest to yours and start there. If you would rather talk it through,book a call.
Connect AI Agents to Company Tools with MCP
Why every AI tool integration becomes a custom job, and how an MCP gateway adds authentication, rate limiting and caching in one place.
Qualify Inbound Leads with AI, Without Blind Trust
A practical guide to AI lead qualification: a deterministic gate, a model that explains its reasoning, and routing that decides the next step in seconds.
Monitoring Production AI: Drift and Hallucinations
AI systems degrade silently. How to trace every call, score answer quality automatically and alert on quality, not just uptime.
Multi-Agent Systems for Business Intelligence
Why one chatbot cannot answer business questions reliably, and how a router, retriever, analyst and validator give verified answers.
Why I Built ByMoin: Architecting Enterprise Agentic AI
I'm Moin Dalal, an Agentic AI Developer & Architect. Discover why I build production-grade agentic AI systems and my vision for AI architecture.