Automation and AI
Automation, data and AI
Processes that stop being manual, scattered data turned into dashboards, and applied AI — including AI that runs inside your own network.
What it covers
Process automation
Scheduled jobs and integrations between systems never meant to talk to each other.
Databases and dashboards
SQL Server, PostgreSQL, MySQL and MongoDB. Modelling and queries, and consolidating old, scattered data stores into a single place you can actually query. From raw data to the dashboard people check every day.
Applied AI
Language models running on-premise, on machines I build and configure end to end: data never leaves the network. Or cloud AI services, when that makes more sense.
Work
CanillitaRunning · GitHub
A personal project. A daily news digest that keeps me current on what matters to an IT professional: AI, technology, data and current affairs. It reads about 25 sources, an AI picks and summarises what matters, and it lands in my inbox every morning. No infrastructure cost.
Management data, end to end
Data scattered across several databases, consolidated and turned into dashboards management checks every day. I model the data, write the query and build the view — no hand-offs in between.
Local model inference
Language models running in-house, on machines I built and configured myself: hardware, operating system, inference server and access.