Reliable self-service analytics
I help data teams turn the reporting bottleneck into trustworthy self-service, for people and AI agents alike.
Self-service was supposed to free your analysts from the ad-hoc SQL treadmill. Instead, answers nobody can trust keep the bottleneck firmly in place. The fix is not a smarter model. It is context.
What I work on
Trustworthy answers from your structured data. Governed semantic and context layers, so a business user and an AI agent reach the same number, to the cent.
Turn unstructured documents into structured data you can actually trust.
The semantic backbone that connects your data, your documents, and your agents.
Featured writing
Reliable self-service is a context problem, not a model problem. The anatomy, layer by layer, built on a zero-cost stack, gaps included.
Read the anatomy →More deep-dives coming: procedural skills and offline evals.
I'm an Analytics Engineer focused on governed self-service analytics.
I build systems where business users, analysts, and AI agents rely on the same trusted metrics and reach the same answers.
My work focuses on making analytics systems robust by making context explicit through semantic layers and metrics governance.
On top of that, I explore how document AI and knowledge graphs can extend structured analytics systems with reliable context for retrieval and reasoning.
Gaël Mukunde