About OmniLayer
We are a Vancouver-based AI company on a mission to make enterprise-grade machine intelligence accessible, responsible, and genuinely transformative for Canadian businesses. Every solution we build is grounded in rigorous science, real-world pragmatism, and a deep respect for the people it serves.
Our Story
OmniLayer was founded in 2019 by a small but formidable group of machine learning engineers and enterprise architects who had spent years inside some of the world's most data-intensive organisations โ including Google Brain, Shopify's AI division, and the University of British Columbia's renowned AI Lab. Frustrated by the gap between cutting-edge research and practical, ethical deployment, they came together in Vancouver with a single conviction: that intelligent systems should work for real businesses and real people, not just for the largest technology companies in the world.
The early years were spent building deep expertise across Canada's most data-rich industries โ retail, healthcare, logistics, and financial services. Rather than chasing quick wins, the founding team invested heavily in proprietary data pipeline architecture and a rigorous model governance framework, ensuring that every solution OmniLayer delivered could be audited, explained, and trusted. That foundation has since become one of our most valued differentiators.
Today, operating from our headquarters at 1055 West Georgia Street in Vancouver, OmniLayer serves over 60 Canadian businesses and processes more than two billion data points every month on behalf of clients. Our team of 34 full-time specialists continues to grow โ but our culture of direct collaboration, scientific rigour, and responsible innovation remains exactly as it was on day one.
What We Stand For
Founded in Vancouver in 2019 by machine learning engineers and enterprise architects with combined experience across Google Brain, Shopify AI, and UBC's AI Lab, OmniLayer was built on a bedrock of academic rigour and industry-tested pragmatism from the very first day.
We have deployed production AI solutions for over 60 Canadian businesses spanning retail, healthcare, logistics, and financial services. Our infrastructure processes more than 2 billion data points monthly โ reliably, securely, and with full client visibility at every stage.
We are committed to responsible AI development and adhere to Canada's Directive on Automated Decision-Making and the federal Artificial Intelligence and Data Act (AIDA) framework in every client engagement. Compliance is not a checkbox โ it is a core design principle.
Our 34 full-time specialists โ data scientists, MLOps engineers, UX designers, and domain experts โ operate in a flat, non-hierarchical structure. Every client has direct access to the people building their solution at every stage of the project, from discovery through to deployment.
Why Clients Choose Us
Canadian businesses in complex, regulated industries trust us because we combine world-class technical depth with genuine accountability and a long-term partnership mindset.
We understand the regulatory landscape that Canadian businesses operate in โ from PIPEDA to AIDA โ and we build compliance into every layer of our solutions rather than bolting it on at the end. Our clients never have to choose between innovation and accountability.
Our team's roots in academic and frontier AI research mean that the models we deploy are not off-the-shelf wrappers. We design, train, and validate custom architectures tailored to each client's data distribution, business logic, and performance requirements.
We define success in the language of business โ revenue uplift, cost reduction, processing time, customer satisfaction โ not model accuracy alone. Every engagement begins with clear KPIs and ends with documented, auditable impact that your stakeholders can understand.
AI is not a one-time project โ it is an evolving capability. Our managed MLOps and continuous improvement services ensure that your models stay accurate, your pipelines stay healthy, and your team stays informed as your business and data landscape change over time.
The People Behind OmniLayer
Our 34 specialists bring together decades of combined experience in machine learning research, enterprise software, and industry domain knowledge. Here are three of the people you are most likely to work with.
Co-Founder & Chief AI Officer
A former research scientist at Google Brain and UBC AI Lab alumna, Danielle leads OmniLayer's model architecture and research strategy, ensuring every solution is grounded in the latest advances in applied machine learning.
Co-Founder & Head of Engineering
Marcus spent six years scaling Shopify's AI infrastructure before co-founding OmniLayer; he oversees the MLOps platform, data pipeline architecture, and the engineering practices that keep client systems running reliably at scale.
Director of Client Strategy
With a background in enterprise consulting for healthcare and financial services across Canada, Sophia translates complex business challenges into clear AI briefs and ensures every OmniLayer engagement delivers measurable, lasting value for clients.
Client Voices
"OmniLayer didn't just build us a model โ they built us a capability. Their team took the time to understand our supply chain in detail, and the forecasting system they delivered has reduced our inventory write-offs by 23% in the first year alone."
"What impressed us most was their commitment to compliance. Working in healthcare, we cannot afford to cut corners on data governance. OmniLayer's AIDA-aligned framework gave our legal and clinical teams genuine confidence from day one."
"The flat team structure is real โ we had direct access to the data scientists and engineers throughout the entire project. There was no account management layer obscuring the work. It made the collaboration faster, sharper, and far more effective."