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Elliptic Labs (ELABS) investor relations material

Elliptic Labs Q3 2025 earnings summary

Complete event summary combining all related documents: earnings call transcript, report, and slide presentation.
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Q3 2025 earnings summary20 Nov, 2025

Executive summary

  • Q3 2025 revenue grew 50% year-over-year to NOK 42.3 million, driven by milestone laptop contracts and increased shipment volumes, with 65% of minimum commitments recognized in the quarter and 25% to be booked in Q4.

  • EBITDA improved to NOK 12.7 million from NOK 0.5 million last year, reflecting strong revenue growth and stable operating costs.

  • Cash position at quarter-end was NOK 54.8 million, supported by positive operating cash flow of NOK 6.5 million.

  • Strategic review initiated by new management to reassess midterm financial targets, product/customer roadmaps, and explore new verticals such as smart glasses.

  • Leadership transitions occurred, with new interim CEO and CFO appointed.

Financial highlights

  • Q3 2025 revenue: NOK 42.3–42.6 million, up 49–50% year-over-year.

  • EBITDA: NOK 12.7 million, up from NOK 0.5 million last year.

  • Net profit for Q3 2025 was NOK 3.9 million, compared to a loss of NOK 4.1 million in Q3 2024.

  • Cash and cash equivalents at quarter-end: NOK 54.8 million.

  • Cumulative nine-month revenue: NOK 93–93.5 million, up from NOK 84 million year-over-year.

Outlook and guidance

  • Double-digit revenue growth for the full year depends on Q4 shipment volumes and contract outcomes.

  • Q4 revenue to be driven by milestone laptop revenues, pay-as-you-go, and new agreements, with 25% of milestone laptop contract revenue to be recognized in Q4.

  • Strategic review underway to reassess midterm revenue targets and commercial priorities.

  • Focus on monetizing existing contracts, expanding with current customers, and increasing sensor deployments per device.

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Frequently asked questions

Norwegian Ultrasound Sensors

Elliptic Labs is a company that specializes in providing virtual smart sensors for a range of electronic devices. Their technology is widely utilized in smartphones, laptops, IoT devices, automotive applications, smart speakers, and televisions. The company uses AI, ultrasound, and sensor fusion to deliver solutions such as 3D gesture recognition, proximity sensing, presence detection, and monitoring of breathing and heartbeats. The company is headquartered in Oslo, Norway, and its shares are listed on the Oslo Stock Exchange.

A Research Spin-off

Elliptic Labs was founded in 2006 by Laila Danielsen, a Norwegian entrepreneur who still acts as the company's CEO. The company emerged from the University of Oslo's research initiatives, focusing on utilizing ultrasound technology for gesture recognition and touchless interaction. The company's early research and development efforts were directed toward integrating ultrasound technology into mobile devices, enabling users to control their gadgets through hand gestures without physical contact.

AI Virtual Smart Sensor Platform

Elliptic Labs' breakthrough came with its AI Virtual Smart Sensor Platform, which has been adopted by major smartphone manufacturers. By eliminating the need for physical sensors, this technology enhances device functionality while reducing hardware costs. Over the years, Elliptic Labs has expanded its applications to include smart home devices, laptops, and automotive systems. The company's technology is in use in over 500 million devices worldwide. Some of Elliptic Labs' publicly traded peers include Synaptics Incorporated, Cirrus Logic, and Infineon Technologies AG.

How it Works and Application Areas

Elliptic Labs' ultrasound-based approach offers several advantages over traditional sensors, including greater flexibility, reduced hardware costs, and the ability to create more intuitive and hygienic user interfaces. The company's technology uses ultrasound to enable touchless interaction with electronic devices. It begins with emitting ultrasonic waves from tiny transducers embedded in the device. When these waves encounter an object, like a user's hand, they reflect back to the device, where transducers capture the returning signals.

These signals undergo advanced processing to analyze the time delay and changes in frequency and amplitude, creating a 3D map of the object's movement. This data is then interpreted by an AI engine trained to recognize specific gestures and movements, such as swipes, waves, or hovers.The AI interprets these gestures and translates them into corresponding commands, allowing users to control their devices without physical contact. For example, users can turn on a screen, adjust the volume, or navigate menus with simple hand movements.

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