Percepto launches Axion AI platform to unify inspection data analysis

Operators can start Axion with their existing inspection data and add Percepto’s autonomous systems and managed remote operations wherever more frequent coverage is needed. | Credit: Percepto

Autonomous drone inspection provider Percepto this week launched Axion, a hardware-agnostic physical AI platform that marks the company’s shift to a software-first strategy. The company said it allows critical infrastructure operators to analyze data from any third-party drone or sensor network to prevent equipment failures before they escalate.

Founded in 2014, Percepto said its initial team built the technology needed for scale. The company asserted that its new management has decades of independent experience with growth across robotics, sensors , the Internet of Things ( IoT ), physical AI , and cybersecurity .

Percepto is based in Modi’in, Israel, with U.S. headquarters in Austin, Texas.

New executives pivot Percepto to software-first strategy

Julien Bellanger recently took the the helm from longtime CEO Dor Abuhasira alongside new revenue and marketing leadership. Percepto said the executive shifts signal its strategic pivot from a hardware-centric autonomous drone maker to a software -first physical AI provider.

“When I looked at Percepto, I saw a company that had already done the hardest part: fully autonomous drones flying real missions every day at some of the most demanding industrial sites in the country,” Bellanger told The Robot Report . “With AIM [Autonomous Inspection & Monitoring] and Axion, we’re taking that operational intelligence beyond our own fleet and opening it to the entire industry.”

The company plans to continue selling, deploying, and supporting its current product line of drones and drone docks. At the same time, manufacturing will be located onshore in the U.S. to support the American Drone Dominance Initiatives .

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Axion extends inspection workflows

Percepto said it has designed the Axion platform to add value to inspection workflows across mission-critical operations, including upstream oil and gas , power transmission and distribution, and most downstream processing facilities.

With Axion, Percepto said it expects to work across the entire industry and to help business grow with AIM’s capabilities. The company is using compliance waivers to control and autonomously fly in one-to-many configurations. Axion will ingest all data sources and provide actionable insights with more than 160 AI models, it claimed.

“The infrastructure powering our economy should benefit from the same advances in AI that are transforming the digital world,” said Bellanger. “Our vision is to provide operators with a trusted understanding of what is happening across their infrastructure, with the foresight to protect the people and operations that depend on it.”

“Axion is the first step in this next chapter, opening our technology to more operators and putting their existing inspection investments to work toward that goal,” he added. “From Day 1, a team can bring the inspection data it already has and see which assets need attention first.”

Available as a software-as-a-service offering, Axion organizes inspection data by asset and applies AI that interprets equipment condition in context. It ingests data from supported third-party drone platforms, fixed and mobile sensors, and existing inspection archives, so operators are not tied to a single hardware provider.

Percept said that Axion can identify a downed wire by its relationship to surrounding components or evaluate a thermal anomaly against expected asset behavior and environmental conditions. Each finding is backed by inspection history and expert validation, giving teams confidence in what needs attention.

In addition, Percepto asserted that Axion enables users to query the corpus of inspection data using plain-language queries. It said its large language model (LLM) enables users to quickly get to the answers that they are seeking and exposes the valuable signals contained in the inspection data.

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