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The FlintCORE Story​

Introducing the Assistant

  • The AI Assistant is integrated in all aspects of the solution.
  • Here we use the Assistant to execute a complex query in a large noise pollution monitoring deployment.
  • The platform can be also be used by people without deep expertise and training. Think of the possibilities here…

 Prompt 1. “Show me the average noise level in the Geneva Cornavin area in April. Weekday measurements shown in teal and weekend measurements in grey.”

 Prompt 2. “Noise limits in Geneva are: daytime (07:00-19:00): 60dBA, evening (19:00-23:00): 55dBA, night (23:00-07:00): 50dBA. Colour in red all measurements above limit.”

 Prompt 3. “Create a device profile for a smart plug that can switch an appliance on/off and monitor energy in real time. Below are the device documentation web links: …”

Built-in programming environment with secure sandboxed execution of custom “event handlers” — acting as a “driver layer” that enables integration with any device or data source, regardless of protocol.

Powerful Analytics with OLAP Database

  • Data available for querying in real time
  • Directly drives operational dashboards and monitoring
  • Handles massive volumes with sub-second analytical performance
  • Open SQL engine — no predefined queries
  • Seamlessly integrated with AI for natural language analytics (via MCP tool)

Highly - customizable dashboards with support for standard visualization types and advanced data graphics using Grammar-of-Graphics frameworks such as Vega, Vega-Lite, Mermaid, others.
These are few examples ;

3DAPARTMENT
3Dsuspensionbridge
bridgehealthsensor
PMlevelsensor
windspeedsensor
tempvisualisation
3dnoisemap
recyclebin
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