Wispr Flow raises $280M at $2 billion valuation to expand AI voice platform

Wispr Flow raised $280 million in a Series B at a $2 billion valuation, giving the AI voice startup fresh capital to improve its speech technology and expand deeper into the workplace.

Menlo Ventures led the round, joined by existing investors Notable Capital, NEA, Neo Ventures, 8VC and MVP Ventures. New investors include Acrew, Forerunner, Goodwater, Peak XV, Together Fund and PLUS Capital. The financing brings Wispr Flow’s total funding to $361 million.

The San Francisco-based startup has attracted some recognizable names outside traditional venture capital. Athletes and cultural figures participating in the round include Livvy Dunne, Shaun White, Dak Prescott, DK Metcalf, Joe Burrow, Kyle Hamilton, Aaron Gordon, Alex Caruso, Domantas Sabonis, Klay Thompson, Paul George and Trae Young.

“Today we’re announcing $280 million in Series B funding at a $2 billion valuation, led by our long-time investor and partner Menlo Ventures. They are joined by existing investors Notable Capital, NEA, Neo Ventures, 8VC, and MVP Ventures,” Wispr Flow said in a blog post.

The round comes less than a year after Wispr Flow raised $25 million in November in a financing led by Notable Capital and backed by podcaster Steven Bartlett’s Flight Fund, according to Reuters. The short gap between rounds reflects the surge of investor money flowing into AI companies that can show real usage and a path into enterprise workflows.

Wispr Flow says its software, which turns speech into text for writing and workplace tasks, has now been used to generate more than 60 billion words. The company says its products are used across nearly all Fortune 500 companies and at more than 10,000 enterprises.

Those numbers help explain why investors are putting a $2 billion price tag on the company. Voice interfaces have existed for years, but generative AI has created a new opening for speech tools that can move beyond basic transcription and become part of how people write, communicate, and work.

Wispr Flow bets on Canto for real-world speech

Alongside the funding announcement, Wispr Flow previewed Canto, its first proprietary speech-recognition model. The company is pitching Canto around a simple problem: speech recognition often looks much better in controlled tests than it performs in real conversation.

“Alongside the funding, we’re announcing a preview of our first proprietary speech model, Canto. Most speech models are trained and evaluated on clean recordings made in a quiet room with a good microphone and an accent the model has heard many times before. Almost nobody lives in those conditions. You’re in a car, on a street, or sitting a foot away from someone else’s conversation in an open office,” CEO Tanay Kothari said.

Kothari says Canto was built to handle background noise, wind, music, and a wider range of accents. According to the company, those difficult conditions can produce error rates above 30% with existing systems, compared with roughly 5% to 10% using its new model.

“We built this model for where people actually use Flow. In the hardest conditions, with background noise, wind, heavy accents or music, error rates fall from more than 30% of words to somewhere between 5% and 10%,” Kothari said in a blog post.

Wispr Flow plans to put much of the $280 million into improving transcription accuracy. Internally, the company tracks what it calls a “zero edit rate,” measuring how much dictated text can be used without requiring corrections.

That metric gets at the bigger challenge facing AI voice products. Speech-to-text is easy to demonstrate under perfect conditions. Getting people to trust it for everyday work, where conversations happen in cars, offices, airports and noisy streets, is a much harder test.

With $361 million raised, a $2 billion valuation and its own speech model now entering the picture, Wispr Flow is betting it can close that gap.