Three former Google X scientists purpose to offer you a second mind nearly — not within the sci-fi or chip-in-your-head sense — however via an AI-powered app that beneficial properties context by listening to every part you say within the background. Their startup, TwinMind, has raised $5.7 million in seed funding and launched an Android model, together with a brand new AI speech mannequin. It additionally has an iPhone model.
Co-founded in March 2024 by Daniel George (CEO) and his former Google X colleagues Sunny Tang and Mahi Karim (each CTOs), TwinMind runs within the background, capturing ambient speech (with person permission) to construct a private data graph.
By turning spoken ideas, conferences, lectures and conversations into structured reminiscence, the app can generate AI-powered notes, to-dos, and solutions. It really works offline, processes audio in real-time to transcribe on-device, and might seize audio constantly for 16–17 hours with out draining the system’s battery, the founders say. The app may also again up person information so conversations could be recovered if the system is misplaced, although customers can opt-out of that. It additionally helps real-time translation in over 100 languages.
TwinMind differentiates itself from AI assembly note-takers like Otter, Granola, and Fireflies by capturing audio passively within the background all day. To make this attainable, the workforce constructed a low-level service in pure Swift that runs natively on the iPhone. In distinction, many rivals use React Native and depend on cloud-based processing, which Apple restricts from working within the background for prolonged durations, George stated in an unique interview.
“We spent about six to seven months final 12 months simply perfecting this audio seize constantly and getting there to search out plenty of hacks round Apple’s walled backyard,” he instructed TechCrunch.
George left Google X in 2020 and received the thought for TwinMind in 2023 when was working at JPMorgan as Vice President and Utilized AI Lead, attending back-to-back conferences every day. To avoid wasting time, he constructed a script that captured audio, transcribed it on his iPad, and fed it into ChatGPT — which started to know his initiatives and even generate usable code. Impressed by the outcomes, he shared it with mates and posted about it on Blind, the place others confirmed curiosity however didn’t need one thing working on their work laptops. That led him to construct an app that might run on a private cellphone, quietly listening throughout conferences to collect helpful context.
Along with the cellular app, TwinMind provides a Chrome extension that gathers extra context via browser exercise. Utilizing imaginative and prescient AI, it will probably visually scan open tabs and interpret content material from numerous platforms, together with electronic mail, Slack, and Notion.
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The startup even used the extension itself to shortlist interns from over 850 functions they acquired this summer season.
“We opened all of the LinkedIn profiles and CVs of the 854 candidates in browser tabs, then requested the Chrome extension to rank one of the best candidates,” George stated. “It did a implausible job — that’s how we employed our closing 4 interns.”
TwinMind provides a Chrome Extension for extra context gatheringPicture Credit:TwinMind
He famous that present AI chatbots — together with OpenAI’s ChatGPT and Anthropic’s Claude — can not simply course of a whole bunch of paperwork or parse sign-ups from instruments like LinkedIn or Gmail to collect contextual info. Equally, AI-powered browsers resembling these from Perplexity and The Browser Firm lack the power to construct data out of your offline conversations and in-person conferences.
The startup presently has over 30,000 customers, with about 15,000 of them lively every month. As a lot as 20–30% of TwinMind customers additionally use the Chrome extension, George stated.
Whereas the U.S. is the most important base for TwinMind thus far, the startup can be seeing traction from India, Brazil, the Philippines, Ethiopia, Kenya, and Europe.
TwinMind targets the overall viewers, though 50–60% of its customers are presently professionals, about 25% are college students, and the remaining 20–25% are people utilizing it for private functions.
George instructed TechCrunch that his father is among the many people utilizing TwinMind to put in writing their autobiography.
One among AI’s vital drawbacks is its potential to compromise person privateness. However George asserted that TwinMind doesn’t prepare its fashions on person information and is designed to work with out sending recordings to the cloud. Not like many different AI note-taking apps, TwinMind doesn’t let customers entry audio recordings later — the audio is deleted on the fly — whereas solely the transcribed textual content is saved domestically within the app, he famous.
Google X expertise helped velocity issues up
The TwinMind co-founders spent a number of years engaged on numerous initiatives at Google X. George instructed TechCrunch that he labored on six initiatives alone, together with iyO — the workforce behind AI-powered earbuds, which lately made headlines for suing OpenAI and Jony Ive. That have helped the TwinMind workforce transfer rapidly from idea to product.
“Google X was really the right place to organize for beginning your personal firm,” stated George. “There are round 30 to 40 startup-like initiatives occurring at any given time. No person else will get to work at six early-stage startups over two or three years earlier than launching their very own — not less than not in such a brief span.”
TwinMind Co-founders Sunny Tang, Daniel George, and Mahi Karim (From Left to Proper)Picture Credit:TwinMind
Earlier than becoming a member of Google, George labored on making use of deep studying to gravitational wave astrophysics as a part of the Nobel Prize–profitable LIGO group on the College of Illinois’ Nationwide Heart for Supercomputing Purposes. He had accomplished his PhD in AI for astrophysics in only one 12 months — on the age of 24 — a feat that led him to hitch Stephen Wolfram’s analysis lab in 2017 as a deep studying and AI researcher.
That early reference to Wolfram got here full circle years later — he ended up writing the primary test for TwinMind, marking his first-ever funding in a startup. The current seed spherical was led by Streamlined Ventures, with participation from Sequoia Capital and different traders, together with Wolfram. The spherical values TwinMind at $60 million post-money.
TwinMind Ear-3 mannequin
Along with its apps and browser extension, TwinMind has additionally launched the TwinMind Ear-3 mannequin, a successor to its present Ear-2, which helps over 140 languages worldwide and has a phrase error fee of 5.26%, the startup stated. The brand new mannequin may also acknowledge completely different audio system in a dialog and has a speaker diarization error fee of three.8%.
The brand new AI mannequin is a fine-tuned mix of a number of open-source fashions, educated on a curated set of human-annotated web information — together with podcasts, movies, and films.
“We discovered that the extra languages you assist, the higher the mannequin will get at understanding accents and regional dialects as a result of it’s coaching on a broader vary of audio system,” George stated.
The mannequin prices $0.23/ hour and can be accessible via an API to builders and enterprises over the following few weeks.
Picture Credit:TwinMind
The Ear-3, not like the Ear-2, doesn’t assist an entire offline expertise, as it’s bigger in dimension and runs on the cloud. Nevertheless, the app robotically switches to Ear-2 if the web goes away after which strikes again to Ear-3 when it’s again, George stated.
With the introduction of the Ear-3, TwinMind now provides a Professional subscription at $15/month, with a bigger context window of as much as 2 million tokens and electronic mail assist inside 24 hours. Nonetheless, the free model nonetheless exists with all the present options together with limitless hours of transcriptions and on-device speech recognition.
The startup presently has a workforce of 11 members. It plans to rent a number of designers to reinforce its person expertise and arrange a enterprise improvement workforce to promote its API. Moreover, there are plans to spend some cash on buying new customers.
