Seeing Machines Ltd (AIM:SEE, OTC:SEEMF) expects to reach cash flow break-even this year after implementing a $12 million reduction in annual operating expenses as part of a company-wide reorganisation aimed at sharpening focus and efficiency.
The London-listed AI-driven transport safety company said it had completed a strategic overhaul of its management structure and cut expenditure across engineering and corporate functions.
These savings, along with a ramp-up in high-margin royalty revenue and growing aftermarket sales, are expected to help the business reach a sustainable breakeven point within the calendar year.
Looking ahead, Seeing Machines anticipates a stronger second half, supported by guaranteed royalty payments and the full-scale launch of its Guardian Generation 3 driver monitoring solution.
Cash flow is expected to improve "significantly" in 2026, as demand accelerates ahead of new EU safety regulations requiring advanced monitoring systems in commercial vehicles from mid-2026.
The company also said its full-year performance is expected to be in line with market expectations, despite some disruption in the global automotive sector.
Chief executive Paul McGlone said Seeing Machines had made "strong operational progress" across its royalty portfolio in the half-year to 31 December.
Production volumes at its automotive partners rose sharply, with more than 2.88 million vehicles now on the road using its technology – up 90% from a year ago.
First-half revenue held steady at $25.3 million, with automotive and aviation income up 27% year on year to $14.5 million. Royalty revenue from car production rose 51% to $6.3 million. Gross profit jumped 32% to $14 million, helped by a better revenue mix and increased licence fees.
Cash at the end of December stood at $39.6 million, up from $23.4 million in June, supported by a $56 million (£26.2 million) investment from Mitsubishi Electric and new partnerships in Europe and the Americas.
The company also completed the acquisition of Asaphus Vision, boosting its AI and machine learning capabilities.