Berlin, Berlin, Germany
Professional services firms are adopting AI fast and governing it slow. The tools on the market either ignore the firm's methodology entirely or hand the expert a summary to rubber-stamp after the fact. We're building the infrastructure that keeps the practitioner in command while the system runs. I was the Enterprise Architect at a global professional services firm. I forced myself onto their AI initiative, proved my approach with working code when another expert estimated ten times the effort, and those prototypes became the internal AI Hub, which is still running strong six months after I left. Two years ago I started building what I called tracaible 😏 observable, testable AI use cases with full lifecycle management. It started on the couch with a CLI tool and a hunch. It turned into a methodology enforcement framework. The thing that kept bothering me: every AI tool for professional services locks the expert out of their own process. You get a blob to approve at the end. No visibility during the run, no risk signals while decisions are being made, no way to challenge the reasoning before the output is final. That's the problem Komplyt solves. Komplyt is the Expertise OS for professional services. The firm's methodology governs every execution through a knowledge graph architecture, dynamic modeling at runtime, and expert-in-the-loop by design. The practitioner stays in command. Every decision is traceable. I run product and engineering. If you want to talk architecture, I'm easy to reach. 📩 [email protected] | kompl.yt
Building the Expertise OS for professional services. I run product and engineering. Built the internal AI Hub at a global PS firm before this. Spent two years developing tracaible, an approach to observable and testable AI lifecycle management that became the methodology core of Komplyt. What I spend my time on: • Knowledge graph architecture for encoding professional methodologies • Dynamic modeling runtime that governs every execution • Expert-in-Command interfaces with inline risk analysis • EU AI Act compliance by architecture • Open-source contributions around agent security and runtime governance
Artificial Intelligence, RPA, Low Code
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