Turn Machine Telemetry into Customer Value
Codd AI provides a contextual semantic layer that gives connected-product telemetry business meaning, so manufacturers can deliver conversational, AI-powered analytics to their customers instead of another dashboard.
Commercial vehicles, industrial equipment, warehouse robots, energy systems, and medical devices generate continuous telemetry: battery levels, operating states, location, odometer readings, charging activity, idle time, and fault conditions. Collecting that data has become straightforward. Turning it into customer intelligence has not. Raw telemetry carries technical information, not business meaning, and the knowledge required to interpret it usually lives inside hand-written SQL, individual dashboard calculations, or the head of a single engineer. As a result, every new customer question becomes another development request, and the more successful the connected product, the heavier the analytical burden on its manufacturer. Codd AI addresses this by capturing operational meaning in a governed contextual semantic layer, so telemetry interpretation, machine relationships, and metric definitions are represented once and reused by dashboards, natural language analytics, AI-generated visualizations, and agents alike.
Key Capabilities
Turn Raw Telemetry into a Common Operational Language
Telemetry describes what a machine reported, not what it means. Codd AI captures how your organization interprets those signals: how odometer readings become distance traveled, how state changes become utilization, how charging behavior affects availability. Machine relationships, reporting intervals, and calculation logic are defined once and governed centrally.
Value: Operational metrics that mean the same thing across every customer, site, and analytical tool.
Let Customers Ask Questions in Natural Language
Fleet and site managers rarely ask the question a dashboard was built to answer. Codd AI lets them ask directly, in their own words, and reason against governed definitions rather than raw sensor tables. Which machines sat idle during the morning shift? Which locations improved utilization this quarter? Where is charging time rising while productive hours fall?
Value: Customers explore their own operational data without every new question becoming an engineering request.
Keep Every Analytical Experience Governed by One Definition
An AI system that understands SQL but not your telemetry can produce a perfectly valid query and a completely wrong answer. Codd AI gives dashboards, natural language interfaces, AI-generated visualizations, and agents a single governed foundation, with full traceability from the answer back to the readings behind it.
Value: Consistent, explainable numbers wherever customers encounter them, and no business logic stranded inside individual dashboards.
Deliver Guided Insight and Proactive Monitoring
Once operational meaning is governed, analytics can move beyond reporting. Agents can watch for machines drifting toward underutilization, sites falling behind their peers, or charging patterns that threaten availability, and surface those findings before a customer thinks to ask.
Value: Analytics shifts from a support cost required by the product to a differentiated capability customers will pay for.