A global manufacturing company needed to consolidate decades of institutional knowledge, disconnected calculators, and compliance documentation into a single system their entire engineering team could use.
This Fortune 500 company operates manufacturing plants worldwide. Their engineering teams relied on a patchwork of disconnected tools, tribal knowledge, and dense compliance documentation that nobody fully understood.
The engineering team was losing time, accuracy, and institutional knowledge every single day. The same problems kept showing up.
The lead subject-matter expert was the only person who fully understood the compliance rubric, the calculators, and which requirements applied to which plants. Her team couldn't function when she was out.
Engineers bounced between Excel spreadsheets, standalone calculators, SharePoint documents, and email threads to get answers. Nothing was connected. Nothing was current.
The audit rubric was dense, technical, and buried in documents nobody read. Engineers didn't know what the auditor actually checked for, what evidence they needed, or how to improve their scores.
New hires spent their first 3+ months in a fog, relying on 1:1 time with senior engineers to learn systems that should have been self-serve.
The team had tried generic AI chatbots before. They made things up. In a compliance context, inaccurate answers aren't just unhelpful, they're a liability.
I built a single web portal that replaced the entire patchwork of disconnected tools. Every widget is grounded in the client's actual documentation, cites its sources, and refuses to invent answers.
Every phase delivered independently usable value. The client saw working software in weeks, not months. No open-ended discovery. No slide decks pretending to be progress.
Deep-dive interviews with the subject-matter expert. Mapped her institutional knowledge into structured, machine-readable data. Identified the highest-value workflows to automate first.
Built a working prototype of the compliance Q&A agent grounded in their actual rubric. Demonstrated it live to the engineering team. Validated accuracy across 10 conversation scenarios.
Expanded from one widget to the full 9-widget portal. Each widget deployed as it was completed so the team started using the system immediately while new features were still being built.
Full source code delivered to the client's IT team. Step-by-step deployment documentation. Training session for internal engineers. Zero vendor lock-in. They own everything.
"The knowledge was always there. It was just trapped in one person's head and buried in documents nobody read. Now it's available to everyone, 24/7."
Katie Dickieson, AI Workflow Architect
Most enterprise AI fails because it's built wrong. Here are the engineering decisions that made this system trustworthy.
Every AI response is anchored to the client's actual documentation. The system cites its sources and refuses to invent answers that aren't in the data.
Off-topic questions are redirected. Ambiguous queries ask for clarification. The system escalates to a human when it doesn't know. No guessing.
Every AI agent was tested against real conversation scenarios including trick questions, edge cases, and attempts to make it hallucinate. Zero failures.
Next.js, TypeScript, Claude API, Supabase. No proprietary frameworks. No magic. The client's IT team can read, modify, and deploy every line of code.
Every engagement starts with a conversation. Tell me what's broken and I'll tell you how I'd fix it.