Co-founders Bruno Machado Valerio and Luciana Prieto take on the roles of Chief AI Officer and VP, Commercial.
AI should change more than the technology a services company delivers. It should change how that company works and what its clients can expect from it.
Elevata is organizing its next chapter around that conviction, appointing Dave Lindon as Chief Executive Officer, Bruno Machado Valerio as Chief AI Officer, and Luciana Prieto as VP, Commercial.
Our direction is clear: make Canada our primary growth market and build an AI-native AWS partner that combines specialist engineering with reusable intellectual property. For clients, that means bringing cloud modernization, data, AI engineering, and operations into one delivery plan.
Leadership built around the next stage
Dave moves into the CEO role after serving as Elevata’s General Manager during its record-breaking third quarter of 2026. A co-founder and former General Manager of the Canadian AWS partner OpsGuru, he helped build the business from inception into a multi-award-winning AWS Premier Tier Services Partner. That experience is directly relevant to Elevata’s next challenge: growing its Canadian business while maintaining technical depth and clear accountability to clients.
Bruno’s appointment as Chief AI Officer gives a co-founder dedicated responsibility for AI strategy across client work and internal operations. Luciana, also a co-founder, leads sales, partnerships, and marketing as VP, Commercial, drawing on her experience with AWS and its partner ecosystem.
This next phase brings together our teams in Canada and Brazil. The cloud architecture, AI engineering, and delivery capabilities supporting our work in Brazil also underpin our expansion in Canada. We are building on that shared foundation as we grow.
Momentum to build on
Elevata closed the third quarter of 2026 with record performance, influencing tens of millions of US dollars in annualized AWS revenue and recording year-over-year growth of up to 2,000% in partner-originated AWS revenue.
AWS remains the foundation of our engineering practice. Our Services Partner relationship with OpenAI adds implementation capabilities that connect AI applications to clients’ existing AWS environments. Our Coralogix partnership extends that work into observability, helping teams understand and manage the systems they run. These relationships support the same objective: delivering technology that works beyond the initial launch.
AI expertise and modernization belong together
An AI application has to work with the data, software, and controls a business already depends on. Selecting a model is only one part of that work. Applications may need to change. Data needs to be accessible and governed. Integrations, infrastructure, and operations need to support the intended use.
Elevata’s engineering practice brings those responsibilities together. We modernize applications and data environments, build AI systems, and address the performance, security, and cost requirements needed to operate them. The AI initiative and the engineering work that makes it viable belong in the same delivery plan.
AI-native delivery changes the business model
Established AWS partners can have deep cloud expertise and still face a different obstacle to AI-native delivery: the economics of their own business. Adding an AI practice expands what they sell. It does not, by itself, change an operating model built around billable effort.
AI and reusable engineering can reduce the work needed to reach a client outcome. For a firm that earns more by selling more effort, that improvement can put existing revenue at risk. For the client, that can mean an AI project delivered through the same model that rewards more billable effort. The hard decision is whether to redesign how work is scoped, delivered, and sold, or keep the old model and add AI to its service catalogue.
Inside Elevata, AI is embedded across our operation, from architecture and delivery to commercial and administrative work. We are prepared to change how that work is delivered and sold as AI and reusable engineering reduce the effort involved.
Expertise should compound, not start over
Our ambition is to pair specialist engineering with proprietary accelerators and reusable solutions, including capabilities designed for particular industries. Each engagement should benefit from what we have already learned and built, while concentrating expert attention on what is specific to the client.
That approach matters in practical areas such as inference architecture and AI cost control on AWS, including Amazon Bedrock and self-hosted inference. Better decisions about how models are deployed and used can help clients balance performance, operating cost, and the demands of a growing workload.
It also changes what a good engagement should look like. Our assessment work starts with the business outcome, the requirements for delivery, and the criteria for success. We identify the data, integrations, access controls, and costs involved in delivery. Those decisions establish what the client is buying and how the result will be evaluated.
Specialist time and judgment remain essential. But time spent is an input, not the outcome.
If AI and reusable engineering allow us to deliver a better result with less effort, that should be progress, not a problem for the business model. Clients should benefit from those advances through a shorter path to useful capabilities, clearer economics, and less unnecessary reinvention.
That is the standard we intend to build Elevata around, and the purpose behind this next chapter in our leadership.
About Elevata
Elevata designs, builds, and operates cloud, data, and AI systems. An AWS Advanced Tier Services Partner with Generative AI and Small and Medium Business Competencies, the company brings together teams in Canada and Brazil and experience delivering more than 400 AWS projects.
Talk to Elevata about moving your next cloud or AI initiative into production.
