Purpose-Built AI for Sensors

predictive
proactive
effective

Combine Edge AI with Action

Enabling deeper insights, less false positives, more trust.

AI at the Edge

We work with advanced sensors, capable inference on the edge. Video, image, or any sensor data is filtered locally, and exceptions handled on the cloud.

Context on the Cloud

Our proprietary model context protocol lets us ingest data from multiple vendors, standardizing and contextualizing the data to drive better insights.

Super Simple IO

Ask what you want. Let AI respond and suggest new questions, or simply address issues. Manage exceptions, not minutiae. Use Flybeam as a dashboard widget or stand alone.
Edge Device
Cloud Context
Inquiry
Resolution


How Flybeam Works:

1. Edge devices run inference or machine intelligence locally.

2. Exceptions are sent to the cloud, where our proprietary Model Context Protocols and training data resolve false positives, and provide context and guardrails.

3. You make an inquiry to your AI agent, such as: “Any cold chain violations upcoming today?”

4. Flybeam finds an issue, and when it does, resolves it. This can be: “Schedule a tech,” or “Flag this in the workforce management app,” or “Call tech now.”


How Enel uses Edge AI 

By analyzing temperature, vibration, and other sensor data from gearboxes and generators, Enel Green Power can detect potential failures weeks or even months in advance.

Predictive maintenance drastically decreases the need for expensive and reactive corrective maintenance, which can cost up to 90% more than planned maintenance.

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