Browse AI is a startup based in Vancouver that is drawing attention for its software-as-a-service platform.
The BC firm’s “no-code web data extraction platform” allows non-technical users to train AI agents that can turn a website into a spreadsheet or data pipeline in minutes.
As one can imagine, this eliminates the need for manual data collection and custom web scraping applications commonly used in gathering market intelligence in e-commerce, real-estate, finance, and other industries.
Pre-built agents are ready to perform basic tasks such as “monitor info on LinkedIn” and “extract products from ProductHunt,” while customization options allow for the creation of advanced workflows.
“Our mission is to democratize access to information on the internet, making it as inclusive as it was intended to be,” Ardy Naghshineh, founder of Browse AI, stated.
Intrigued by Naghshineh’s vision, investors have made their mark.
Browse AI announced this week that it has secured just shy of US$3 million from a range of venture capitalists and angels.
“This seed funding enables us to scale faster and give millions of individuals and SMBs an equal opportunity to benefit from the vast amount of ever-changing online information,” Naghshineh noted.
Contributing to the seed round was Interface Capital, Alpine Venture Capital, AltaIR, Banana Capital, Creator Ventures, Trust Fund, Singularity Capital, and Goodwater Capital, as well as Evan Moore and Arash Ferdowsi, co-founders of DoorDash and Dropbox.
One investor described Browse AI as a “next-generation data company” that has already been able to achieve “a lot with very little capital.”
Browse AI gained nearly a quarter million new users within the past half year, according to a statement from the now-profitable startup, adding that recurring revenues have grown tremendously year-over-year.
Naghshineh points to a “timely convergence” of tech and trends, such as machine learning algorithms and rapid digital transformation, which “paved the way for a solution like Browse AI.”
“From day one, we recognized that machine learning and crowdsourcing training data at scale are absolutely essential for achieving a fully automated solution adaptable to every website that requires zero maintenance,” explains the chief executive officer.
Already, the platform has automated more than 11 million tasks, saving users a combined 17 million hours of manual effort, according to an online tracker.
“The first phase of our strategy was to build the easiest way for users to train robots and focus on network effects to attract a critical mass of early users,” says Naghshineh.
The key of the next phase for Browse AI is to automate more of the process—to eventually take users from quick sign up to complex workflow automations within minutes.
Founded in 2020, Browse AI ran through a pre-accelerator in Edmonton, then an accelerator in San Francisco, before launching on ProductHunt in 2o21.