Arauco seeks better efficiency in material handling through lift trucks retrofitted by Cyngn

A vendor of industrial driving solutions has received an order for 100 of its AI-powered autonomous electric forklifts, according to Menlo Park, California-based Cyngn Inc.

Deliveries are targeted to begin in 2024 to Arauco, a wood products supplier that had over $7 billion in revenue in 2022. Arauco said its goal is to enhance operations and drive efficiency in its material handling processes, supporting the company’s business of supplying sustainable forestry products, pulp, and engineered wood to the furniture and construction industries.

Arauco said it will deploy the new vehicles to address the challenge of automating heavy loads—weighing over 10,000 pounds—with non-standard pallet pockets, which was previously unmet by other industrial autonomy providers.

The dollar value of the deal was not disclosed, but Cyngn said that while the initial pre-order of 100 autonomous electric forklifts refers to only a small portion of Arauco's existing fleet, it represents a meaningful initial annual recurring revenue deployment for Cyngn. The firm said that new revenue could cover up to approximately 20% of its current monthly cash burn, demonstrating the potential for growth and expansion.

The forklift manufacturer was also not disclosed, but Cyngn’s press release showed photographs of autonomous lift trucks from the Chinese electric vehicle manufacturer BYD.

Cyngn creates autonomous forklifts by installing its DriveMod Kit on new industrial vehicles at end of line or via retrofit, empowering customers to seamlessly adopt self-driving technology into their operations without high upfront costs or the need to completely replace existing vehicle investments. The firm’s flagship product, its Enterprise Autonomy Suite, includes DriveMod (autonomous vehicle system), Cyngn Insight (customer-facing suite of AV fleet management, teleoperation, and analytics tools), and Cyngn Evolve (an internal toolkit that enables Cyngn to leverage data from the field for artificial intelligence, simulation, and modeling).