Overview

AI Analytics turns metering-node telemetry into ready-to-use reports for decision making. Instead of exporting device data by hand and assembling spreadsheets, you select a report, set its scope (company, node, period) and receive a finished document with figures, charts and conclusions.

Deterministic core, AI as an explanation layer

Every report is built on a deterministic analytical core: each key conclusion — archive quality, period readiness for closure, data freshness, uncovered-volume estimate, Q/V reconciliation, sensor stability, link state, passport completeness, incidents and recommendations — has a formal origin, is computed by defined formulas and reproduces exactly when re-run on the same data.

AI is used as an auxiliary language layer. It briefly explains already-computed results in plain language, summarizes the deterministic indicators and produces readable commentary. It does not replace the formulas, establish facts, or decide statuses — final report statuses are determined by rules, thresholds and archive data.

Two levels of reports

Reports answer at two levels. Node-level reports cover a single device or object — its consumption profile, battery life, pressure behavior. Fleet-level reports cover an entire fleet or a selected company — the most problematic nodes, the largest leaks, the economics of automation.

Trust and limits

Reports are a management and operational assessment for prioritizing decisions — not an accounting or metrological act. Every figure is tagged with a confidence level (confirmed, scenario or possible), so estimates are never passed off as measured facts. See the methodology for the full set of principles.