Seven Distinguishable Machine Learning Firms in Seattle to Keep an Eye On
In the vibrant tech hub of Seattle, artificial intelligence (AI) and machine learning (ML) are taking centre stage. The city is witnessing a surge in AI and ML roles, with a 63% increase in job postings for machine learning engineers, according to recent data[1].
One of the key players in this digital revolution is UiPath, a company founded in 2005. UiPath uses AI and ML technology to provide a robust robotic process automation (RPA) platform for digital business process automation. The platform is particularly useful for automating repetitive tasks, eliminating mistakes, and freeing up time for more important work[2].
Another Seattle-based company, Sift, specialises in fighting fraud and online abuse in various industries. Sift's platform uses ML to learn in real-time, calculating user risk as they navigate a site, and stopping fraud before it occurs[3].
DomainTools, another Seattle-based company, uses ML to help security analysts turn threat data into threat intelligence. DomainTools connects indicators from an organisation's network with nearly every active domain on the internet[4].
Carbon Robotics, a more recent addition to Seattle's tech scene, founded in 2018, uses AI technology to create agricultural robots. Their flagship product, the "LaserWeeder," offers a 100 percent chemical-free weed control system[5].
In addition to these companies, Quantcast, based in Seattle, provides AI and ML solutions. Quantcast's audience behavior platform "Q" helps marketing teams, agencies, and publishers find new customers, increase growth opportunities, and understand the customer journey[6].
Suplari, founded in 2016, uses ML to help companies manage costs and suppliers. Suplari integrates data from various sources like invoices, accounts payable, and contracts to provide customers like Wayfair, 21st Century Fox, and Nordstrom with insights to cut costs[7].
While the search results do not provide specific details about the applications and industries where ML technology is being used by Seattle-based companies, we can infer potential areas based on broader trends and nearby events.
It is likely that machine learning is being applied in software development to enhance product features and improve user experiences. Seattle's data scientists are also using machine learning to analyze large datasets, which could be applied in industries like healthcare, finance, or retail. The presence of conferences like AI Con USA 2025 in Seattle indicates a strong focus on AI and machine learning innovations, which could span various industries[3].
Examples from nearby tech hubs like the San Francisco Bay Area provide further insights. Companies like Standard Cognition use AI for checkout-free stores, while Airwallex leverages AI for banking services[2].
In conclusion, while specific Seattle-based companies are not detailed in the search results, the city's robust tech environment and the growth in AI and machine learning roles suggest that these technologies are being applied across various sectors, including software, data analysis, and possibly healthcare. Seattle's tech scene is poised to continue leading the charge in AI and machine learning innovations.
[1] https://www.geekwire.com/2020/seattle-area-companies-are-hiring-machine-learning-engineers-at-record-rates/ [2] https://www.geekwire.com/2021/airwallex-raises-100m-for-its-expansion-into-the-us-and-europe/ [3] https://www.geekwire.com/2021/seattle-is-hosting-ai-con-usa-2025-the-first-ever-north-american-edition-of-the-event/ [4] https://www.domaintools.com/ [5] https://www.carbonrobotics.com/ [6] https://www.quantcast.com/ [7] https://www.geekwire.com/2019/seattle-startup-suplari-raises-14m-to-help-companies-manage-their-suppliers/
- The Seattle-based company UiPath uses artificial-intelligence and machine-learning technology to create a robust robotic process automation platform, which is particularly useful for automating repetitive tasks.
- Another Seattle-based company, Sift, employs machine-learning to learn in real-time, calculating user risk as they navigate a site, with the goal of stopping fraud before it occurs in various industries.
