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Draganfly (DPRO) Q2 2026 earnings summary

Event summary combining transcript, slides, and related documents.

Logotype for Draganfly Inc

Q2 2026 earnings summary

21 Aug, 2026

Executive summary

  • Achieved record Q2 2026 revenue of CAD 2.7 million (USD 2.66 million), up 26% year-over-year, driven by strong product sales and strategic market positioning.

  • Secured exclusive partnerships with IACLEA and the Small & Rural Association, expanding reach into campus and rural law enforcement markets.

  • Completed the acquisition of Skip Dynamix, enhancing fixed-wing drone capabilities and government contacts.

  • Awarded a significant DEVCOM contract for an ultra-light, modular counter-drone system, positioning for substantial future revenue.

  • Gross profit rose to CAD 533,149 (USD 533K), though gross margin declined due to sales mix and a one-time inventory write-down.

Financial highlights

  • Q2 2026 revenue was CAD 2.7 million (USD 2,664,237), with product sales contributing CAD 2.6 million and six-month revenue at USD 4,976,590.

  • Gross margin for Q2 2026 was 20.0% (adjusted: 21.7%), down from 23.9% (24.3%) year-over-year.

  • Total comprehensive loss increased to CAD 11.8 million (USD 11.83M), mainly due to higher operating costs and non-cash items.

  • Cash balance at quarter end was CAD 131.9 million (USD 131.9M), up from CAD 90.2 million at 2025 year-end.

  • Shareholder equity increased to CAD 148.9 million (USD 148.9M) from CAD 96.6 million at year-end.

Outlook and guidance

  • Anticipates significant procurement and revenue growth from Canadian and NATO markets by year-end, with a measured approach to scaling operations.

  • Management expects continued demand for secure, high-performance imaging and drone systems, supported by new product launches and defense contracts.

  • Plans further product rollouts and expects sizable orders from new partnerships and technology acquisitions.

  • Forward-looking statements highlight growth opportunities but caution significant business and economic uncertainties.

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