Palladyne AI Q4 Earnings Call Highlights

Palladyne AI (NASDAQ:PDYN) management used its fourth-quarter and year-end 2025 earnings call to reiterate its 2026 revenue outlook, discuss an increase in backlog early in 2026, and outline how the company expects its recently completed acquisitions to reshape operations and go-to-market execution.

2026 guidance reiterated; backlog rises early in Q1

President and CEO Ben Wolfe said the company is reiterating its 2026 revenue guidance of $24 million to $27 million, which he characterized as roughly four to five times 2025 revenue. Wolfe also said backlog increased from approximately $13.5 million at the end of 2025 to nearly $18 million midway through the first quarter, attributing the change to new contract wins net of normal invoicing activity.

Management emphasized that 2026 will be the first full year reflecting the company’s structural changes following acquisitions completed in mid-November 2025.

Management frames 2025 as “validation” then “transformation”

Wolfe described 2025 in two phases. In the first three quarters, he said the company focused on “validation,” upgrading Palladyne IQ based on feedback from the U.S. Air Force and potential Fortune 100 customers and developing what became Palladyne IQ 2.0. Wolfe said IQ 2.0 was completed and began being shown to customers in early January, and that the effort resulted in the company’s first signed commercial IQ customer contract a couple of weeks prior to the call. Management said the deal was not financially material but was strategically important, and that it was signed through a systems integration partner deploying IQ for robotic surface preparation.

In parallel, Wolfe said Palladyne advanced its collaborative autonomous drone product, Palladyne Pilot, and created a swarming variant branded SwarmOS for Defense and National Security. He cited MOUs signed with Red Cat and Draganfly, as well as expanded capabilities through military development contracts.

Wolfe said the second phase began in November with the acquisition of GuideTech, Warnke Precision Machining, and MKR Fabricators, alongside the launch of Palladyne Defense. He said the acquisitions added avionics design and engineering, proprietary UAV and missile systems, precision components, certified U.S.-based manufacturing, and backlog, moving Palladyne from primarily a development-stage AI company to a vertically integrated industrial and defense platform generating “meaningful revenues.”

Product focus: edge autonomy, swarming, and space domain expansion

Wolfe used the call to differentiate Palladyne’s “biologically inspired” AI architecture, arguing that real-world systems such as drones and robots require edge-based autonomy rather than dependence on centralized cloud computing. He said the company published a white paper (with co-founder Dr. Garagić) outlining this approach.

He said SwarmOS enables decentralized collaboration at the edge, and that IntelliSwarm combines SwarmOS with the company’s BRAIN X2 avionics platform to provide an integrated hardware-and-software stack for drones and missiles. Wolfe also said the company branded Project Banshee as Gremlin-X and advanced development of a “mini bomber drone concept.” He noted a successful demonstration of a cross-platform coordinated swarm using IntelliSwarm on Gremlin-X and SwarmOS on Red Cat drones, which he described as “true autonomous swarming.”

Wolfe also said the company is extending its distributed autonomy model into the space domain through development work with the Air Force Research Lab, expanding SwarmOS to incorporate satellites as additional sensor nodes. Separately, he said Palladyne expanded its relationship with Portal Space Systems, providing navigation, guidance, spacecraft modeling, embedded software, and avionics support for next-generation space logistics platforms.

Missile and manufacturing: new contract cited

On the manufacturing side, Wolfe said Palladyne recently secured a missile propulsion subsystem contract from a “major defense prime customer,” calling it validation of propulsion, engineering, and manufacturing capabilities and saying it would generate revenue in 2026.

During Q&A, Wolfe added that the company sees opportunities across both new missile efforts and as a supplier into existing missile programs. He described interest in higher quantities of lower-cost, higher-precision missiles and said Palladyne can participate “soup to nuts,” from concept design through manufacturing of complete systems or subsystems.

Financial results: acquisition-driven revenue lift, operating loss, and liquidity

CFO Trevor Thatcher said the reported fourth-quarter and full-year results included approximately six weeks of contribution from the mid-November acquisitions.

  • Q4 revenue: $1.7 million, up 118% from $0.8 million a year earlier, driven by post-acquisition revenue from the acquired companies.
  • Cost of revenue: $1.4 million vs. $0.6 million in the prior-year quarter.
  • R&D expense: $3.8 million vs. $2.6 million, reflecting investment in autonomy software, avionics, and product development programs.
  • G&A expense: $4.7 million vs. $3.5 million, driven by acquisition transaction costs, expanded G&A scope, and compensation normalization at acquired businesses.
  • Sales and marketing expense: $1.0 million vs. $0.6 million, reflecting expanded marketing and business development.
  • Operating loss: $9.3 million vs. $6.5 million in the prior-year quarter.
  • GAAP net loss: $1.5 million, or $0.04 per share.
  • Non-GAAP net loss: $6.9 million, or $0.16 per share.

Thatcher said the main differences between GAAP and non-GAAP results included a $46 million non-cash gain tied to the change in fair value of warrant liabilities, $1.1 million of stock-based compensation expense, $0.6 million of acquisition-related transaction expenses, and a $2.5 million income tax benefit linked to one of the November acquisitions.

As of December 31, 2025, the company reported approximately $47 million in cash, equivalents, and marketable securities. Thatcher said the company’s fourth-quarter net cash burn rate was approximately $10 million, including $8.5 million used in operations, $5.3 million used for acquisitions, and $3.7 million to pay down real estate debt assumed in the acquisitions, offset by about $7.3 million in net proceeds from ATM sales.

Looking to 2026, Thatcher said the company expects consolidated quarterly operating cash usage of approximately $8 million to $9 million, reflecting investment in SwarmOS and IQ, investments to bring acquired programs to operational readiness, and headcount additions to build defense and commercial team structures. He said Palladyne previously indicated plans to invest $5 million in Gremlin-X and Project SwarmStrike over the next 12 to 18 months.

In Q&A, management declined to break out revenue guidance by segment and said it was not providing guidance below revenue at this time. Wolfe said the company still expects “software-like” margins for the AI business and said the hardware side is focused on higher-margin opportunities.

On partnerships, Wolfe said the company expects its swarming software to be certified on Red Cat drones “virtually any time” and said a broader implementation agreement was expected to be signed imminently. For Draganfly, he said porting code to platforms was in process and expected to be completed during the quarter. Wolfe also said the company expects SwarmOS licensing to be priced on a per-drone basis, historically targeting 5% to 10% of total drone system cost, while noting the company still needs to land its first major customer for the platform.

About Palladyne AI (NASDAQ:PDYN)

Palladyne AI Corp., a software company, focuses on delivering software that enhances the utility and functionality of third-party stationary and mobile robotic systems in the United States. Its Artificial Intelligence (AI)/ Machine Learning (ML) software platform enables robots to observe, learn, reason, and act in structured and unstructured environments. The company's software platform enables robotic systems to perceive their environment and quickly adapt to changing circumstances by generalizing from their experience using dynamic real-time operations without extensive programming and with minimal robot training.

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