iiSP
A concept for accessible AI integration
“AI adoption shouldn't require an enterprise budget — it should start with tools you've actually built.”
iiSP is a personal project exploring how Canadian small and mid-sized businesses could adopt AI in ways that actually make sense — not hype-driven chatbot widgets, but genuine integration of RAG systems, intelligent agents, and orchestration layers into existing business workflows. I've built the prototypes and documented the approach as a proof of concept.
The Problem
What needed solving
Canadian SMBs keep hearing that AI will transform their business, but when they look for help, they find two extremes. On one side, enterprise consultancies charge six figures for custom AI deployments that take months. On the other, off-the-shelf chatbot widgets that hallucinate about products they've never seen and add no real business value.
What's missing is a practical, affordable approach that understands both the technology and the reality of running a small business — one that assesses where AI actually fits into existing operations, builds solutions that integrate with what's already working, and delivers measurable outcomes without a massive upfront investment.
The Solution
How I approached it
The iiSP concept centres on three service areas: RAG-powered knowledge systems that turn a company's existing documents into intelligent, searchable assistants; AI agent development that automates repetitive business processes; and orchestration design that connects these pieces into a company's existing workflows.
The key principle is practitioner-led design. Every prototype I've built for iiSP uses technology I developed and tested myself — from a RAG chatbot that answers questions using a business's own documents, to a CRM prototype with AI-powered lead scoring. The approach is grounded in tools I've actually built, not theoretical recommendations.
How It Works
Under the hood
The concept starts with assessment — identifying where AI can genuinely improve a business's operations, not where it sounds impressive, but where it delivers measurable value. The prototypes I've built demonstrate the core capabilities.
For knowledge management, I've built systems that index documents (PDFs, spreadsheets, Word docs, images) and deploy a RAG-powered assistant that answers questions grounded in actual content — with source citations, not hallucinations. For process automation, I've prototyped AI agents tailored to specific business workflows. For deeper integration, I've designed orchestration patterns that connect AI tools with existing systems.
The prototypes include a CRM and analytics dashboard, demonstrating how businesses could track AI performance, score leads on technical maturity, and make data-driven decisions about AI investment.
Impact
Results and outcomes
iiSP represents the intersection of everything I've built — the systems thinking from twenty years of infrastructure work, the AI tooling expertise from projects like ContextLens and TARA, and the product development discipline from ListingRocket. It's a concept built on the belief that AI adoption shouldn't require an enterprise budget.
Every prototype demonstrates technology I developed, tested, and use in my own projects. That's the core thesis — practical AI integration built on first-hand experience, not resold tooling.