- Headquartered in Australia, the company maintains a range of global clients across Australia, Southeast Asia and Europe
- Trellis Data’s technology is currently deployed to multiple sectors, including government, defense, law enforcement, and logistics
- Entry into the US market is the result of investment from Ultratech Capital Partners
ARLINGTON, Va., March 9, 2023 /PRNewswire/ — Advanced machine learning company Trellis Data announces its entry into the United States, opening an office in Arlington, VA, after a new round of funding Ultratech Capital Partners, a specialist US investment arm of Damazein Family Office. The new round of funding catalyzes Australia-based Trellis Data’s US market entry and supports further deployment of its AI technology already in use across government, defense, law enforcement, and logistics sectors.
Trellis Data’s new round of funding marks its first international office, expanding upon its current client base spanning Australia, Southeast Asia and Europe.
According to Michael Gately, CEO of Trellis Data, "Trellis Data is leading the way in trusted AI by providing real-time explanations for deep neural networks. Our explanation technology is cutting edge and sits at the core of our Trellis Intelligence Platform (TIP), producing results across all our models and data types."
TIP has been developed with a wide user base in mind. With a ‘no-code’ approach to machine learning solutions, TIP is designed to make building models faster and easier, helping organizations to use AI to solve more complex business problems.
"At Trellis Data we want to democratize machine learning. We believe you shouldn’t have to be a data scientist to leverage the power of AI and produce meaningful results. Our technology is already a proven success in Australia, and we’re excited to bring our innovative, disruptive solutions to customers in the United States. Trellis Data is ideally positioned to lead the growth of the sector," added Gately.
Trellis Data specialises in using computer vision for object detection, as well as understanding natural language processing to produce highly accurate speech-to-text and translation. By partnering with its customers and service providers, the company delivers AI technology that can tackle complex real-world problems.
For example, as part of its suite of practical solutions:
- Trellis Data has developed sophisticated scene text reading models to streamline logistics operations by scanning hard-to-read surfaces and autonomously identifying shipping containers, trucks, and pallets.
- Trellis Data aids law enforcement by enhancing surveillance through highly accurate transcription and translation models that can listen for defined keywords and phrases faster than real-time.
- In a world first, Trellis Data is also helping to protect Australia’s agriculture sector from biosecurity threats as part of a trial to use advanced object detection models to detect invasive plants and pests.
"The opportunities of machine learning are now being realized around the globe and organizations are demanding AI tools that are straightforward to use, that can integrate with existing enterprise systems, and, most importantly, produce results they can trust. We see immense opportunity to expand our technology adoption in the United States," Gately said.
"The US is a key market for the growth of machine learning. This expansion means our existing clients with operations in the US will benefit from having our team on the ground, and US-based companies will have access to the world-leading machine learning and artificial intelligence we provide."
About Trellis Data
Trellis Data delivers the world’s most sophisticated machine learning that can be trusted, on an easy to use Machine Learning platform. Our core product is the Trellis Intelligence Platform (TIP) – an enterprise-scale, deep learning platform that enables both deep learning experts and non-expert users to solve complex problems by creating, training, and deploying trusted deep learning solutions. TIP is delivered as a Software-as-a-Service that spans the end-to-end requirements for organizations seeking to use machine learning.
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