News
Treble raises $18 million more for its voice simulation platform
Funding brings total above $40 million for synthetic speech data

- September 17, 2026
- Updated: September 17, 2026 at 9:20 AM

Treble, the Icelandic startup behind voice simulation software, said today that it has raised $18 million in a Series A extension from Paladin Capital Group, KOMPAS VC, Frumtak Ventures, EIC, and Omega ehf. That brings its total funding to more than $40 million, following a $12 million investment in 2024. The company pitches its physics-based platform as foundational infrastructure for speech systems, robots, and connected devices. The idea is to model speech in real-world spaces, not scraped internet recordings, so teams can deal with the data problems that show up in noisy conditions.
Treble generates synthetic data for speech enhancement, noise suppression, and model training. It also gives companies a way to test performance before a product ships. On top of that, the platform can be used to prototype headphones, speakers, smart speakers, smart glasses, and other voice hardware by simulating room placement, how the device is worn, and the kind of background noise it will have to handle.
The company also says it’s picking up momentum. Amazon and Logitech are listed as customers, Treble has teamed up with Hugging Face on a more realistic speech-recognition benchmark, and Treble says its simulation runs more than 100 times faster than existing approaches.
If you’re building always-on voice products, this looks like a company to keep an eye on. Market forecasts put the sector at $3.6 billion in 2023 and $21.8 billion by 2030, with particular interest around wearables that can isolate voices in places like restaurants or seminars, even as bias, privacy, deepfake, and fraud concerns hang over the category.
You can find Treble on the company’s website.
Jesús Pina follows what artificial intelligence is actually changing in the software people use every day, telling apart what already works from what is still only an announcement. What interests him is the practical effect: which tool saves real time, which one stops halfway and which one deserves a second look before you install it. He works daily with AI models inside Softonic's own editorial process, so he knows their limits fairly well.
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