Built at Data Sovereignty & Responsible AI · submitted 20 September 2026
Norrin Trustworthy Process Monitor takes an undocumented table of sensor readings - any format, no labels, no documentation, gigabytes if needed - and explains in plain language what each column is, whether the data can be trusted, when the process behaved unusually, and why. It runs the entire analysis on your own computer: the default profile makes no network call at all, and the optional Claude and EU-hosted routes send only aggregated, rounded and anonymised results through a guard that inspects every payload and records it in a ledger. Raw readings never leave the machine. Seven stages build on each other: understanding the columns and how sensors move together, data quality, monitoring for drift and sudden changes, a ranked diagnosis challenged by a built-in critique, an assessor that says whether more data would help, reports in HTML, PDF, PowerPoint and e-mail, and a live monitor for a running feed. Every page opens with a short summary and next steps, with charts, tables and evidence behind "Show technical analyses", in Basic, Operator and Engineer modes and in English, Finnish and Swedish. A person can accept, question or override any conclusion, rename a sensor, write operating rules in plain English and ask "why?" in a chat that counts from the run's own artifacts, and every decision lands in a tamper-evident log. The app is built to be checked rather than believed: where a list stops at a limit it says so and gives the true total, a finding its own critique weakened can never be called "very sure", and every score states what it measures. When the data happens to carry a truth column, it scores its own detection - precision, recall, detection delay - and says plainly what those numbers mean. It installs on Windows in minutes with no Python, no administrator rights, no account and no API key; with a local model (Ollama) the explanations are written on your machine, and without one it says so and keeps working.
