Last updated 15 June 2026

Epirus vs D-Fend Solutions

Opposite ends of the non-kinetic counter-drone spectrum: high-power microwave area defeat versus radio-frequency cyber takeover of a single target.

Epirus and D-Fend Solutions are both non-kinetic counter-drone specialists, which makes them easy to group together and wrong to treat as alternatives. Epirus builds Leonidas, a software-defined high-power microwave system that disables the electronics of many drones at once, the answer to saturating swarms. D-Fend builds EnforceAir, an RF cyber-takeover system that assumes control of a single rogue drone and lands it safely without jamming or collateral disruption. One is an area effect for the swarm problem; the other is a precision effect for the urban single-intruder problem.

Side By Side

EpirusD-Fend Solutions
Founded20182017
HeadquartersTorrance, California, USARa'anana, Israel
StatusPrivatePrivate
Total Funding$550 million+ (Series D $250M, March 2025)$67 million ($31M growth round, December 2024)
Notable Investors8VC, General Dynamics Land Systems, T. Rowe Price-advised fundsIsrael Growth Partners, Vertex Ventures
FlagshipLeonidas, software-defined high-power microwaveEnforceAir, RF cyber-takeover
Defeat MethodNon-kinetic directed energy; disables onboard electronicsNon-kinetic cyber takeover; assumes positive control of the drone
Engagement ProfileArea effect; multiple targets per engagement (swarm defeat)Single target; controlled landing and recovery
Collateral ProfileAffects unshielded electronics within the beam pathMinimal; selective protocol manipulation, no broadband jamming
NDAA / Federal ProcurementCompliant; counter-swarm programme positioningPartial (Israeli supply chain); deployed by US federal agencies

AREA DEFEAT VS PRECISION CAPTURE

Epirus exists to solve the economics of saturation. A single Leonidas pulse can disable multiple inbound drones with no consumable munition per kill, which is the only counter-UAS cost model that scales against massed attack-drone raids. The cost of that breadth is that high-power microwave is an area effect: it acts on unshielded electronics within the beam, so it is suited to military air defence rather than to surgical use around sensitive systems.

D-Fend sits at the opposite end. EnforceAir identifies a target drone's control protocol, takes over, and lands it under positive control, with no jamming and no kinetic debris. That precision makes it the fielded option for urban environments, sensitive infrastructure, and protective details, and it preserves the captured drone for forensics and operator attribution. The constraint is the inverse of Epirus's: it is a one-target-at-a-time effect that depends on protocol coverage of the threat drone, which is broad for commercial platforms but not guaranteed for bespoke builds.

PROCUREMENT FIT

Epirus fits the military counter-swarm mission. The March 2025 $250 million Series D, taking total funding past $550 million with General Dynamics Land Systems as a strategic investor, positions Leonidas as integration-grade for vehicle-mounted and fixed air defence ahead of the procurement cycle.

D-Fend fits the federal law-enforcement and urban-security mission, where collateral radio-frequency disruption is unacceptable and where capturing rather than destroying the target carries investigative value. The two are complementary layers in an integrated architecture far more often than they are competing bids for the same requirement.

When To Choose

Choose Epirus if:

  • Defeating saturating drone swarms cost-effectively
  • Military, vehicle-mounted, or fixed air defence
  • Non-kinetic effect with no per-target munition cost

Choose D-Fend Solutions if:

  • Urban or sensitive environments where collateral disruption is unacceptable
  • Single rogue-drone capture with positive control and safe landing
  • Mission includes attribution, forensics, or preserving the target drone

Full Profiles

Drone Intelligence, Comparison. Compiled from public filings, primary sources, and verified disclosures. Last updated 15 June 2026.

paul@droneintelligence.ai