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SoundHound
🇺🇸 NASDAQ:SOUN
•
Dec 31, 2024

SoundHound Q4 2024 Earnings Report

SoundHound AI reported record revenue growth in Q4 2024, doubling year-over-year and exceeding expectations.

Key Takeaways

SoundHound AI delivered an exceptional Q4 2024 performance, achieving record revenue of $34.5 million, a 101% increase compared to the previous year. Despite strong topline growth, the company reported a GAAP net loss of $258.6 million, largely impacted by non-cash fair value adjustments. Adjusted EBITDA stood at -$16.8 million, reflecting continued investment in AI-driven voice solutions. The company ended the quarter with a strong cash position of $198 million and no debt.

Revenue surged 101% YoY to $34.5 million, exceeding expectations.

GAAP EPS was -$0.69, while non-GAAP EPS was -$0.05.

Adjusted EBITDA loss of $16.8 million reflects continued investments.

Cash and cash equivalents stood at $198 million with no outstanding debt.

Total Revenue
$34.5M
Previous year: $17.1M
+101.5%
EPS
-$0.05
Previous year: -$0.07
-28.6%
Gross Profit
$13.8M
Previous year: $13.2M
+4.1%
Cash and Equivalents
$198M
Previous year: $109M
+81.7%

SoundHound Revenue

SoundHound EPS

Forward Guidance

SoundHound AI raised its full-year 2025 revenue outlook to a range of $157M to $177M, anticipating continued strong demand for its voice AI solutions.

Positive Outlook

  • Full-year 2025 revenue guidance increased to $157M - $177M.
  • AI-driven product adoption continues to expand across multiple industries.
  • Strong cash position enables further strategic investments.
  • Expanding partnerships with major brands in QSR, automotive, and healthcare sectors.
  • Advancing AI capabilities with new generative AI innovations.

Challenges Ahead

  • Continued losses expected as investment in growth initiatives remains high.
  • Competitive pressures in the AI and voice assistant market persist.
  • Macroeconomic uncertainty may impact enterprise spending on AI solutions.
  • Stock price volatility affecting fair value adjustments and reported earnings.
  • Execution risks in scaling AI deployments across industries.