Become AI Native

We help organizations move along the AI maturity curve, from their first experiments to AI Native. Through measurement, governance, training, and engineering, we help you make AI part of everyday work and turn its potential into measurable business results.

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The AI Maturity Curve. The horizontal axis shows increasing AI Maturity from left to right; the vertical axis shows increasing Business Impact from bottom to top. An illustrative exponential curve rises gently at first, then increasingly steeply through five stages. Newcomer: AI is not yet part of the organization’s everyday work. Explorer: people try AI tools and find useful ways to apply them. Experimenter: teams test AI pilots on real tasks and measure their value. Adopter: teams embed proven AI tools into their everyday workflows. AI Native: AI shapes how work is designed, measured, and improved. Each stage has a marker linked to its label and description below the curve. The AI Native endpoint is highlighted in orange. The chart is conceptual, with no numerical scale or guaranteed business returns.

How we help

Measurement

Measure the return.

Our team has measured returns on AI projects across industries, including capital markets, manufacturing, marketing, and the public sector. We help you understand whether your AI investments are paying off, decide where to invest next, and give executives, boards, and investors clear evidence of the results.

Governance

Coordinate your AI efforts.

Our team has led AI initiatives for Toyota, Verizon, and other enterprise clients. We help you decide what to centralize, where to encourage experimentation, and how to bring one team’s successes across the organization. Together, we establish ownership and standards for shared AI tools and a roadmap for what comes next.

Training

Build your team’s AI skills.

Our team includes professors and strategic consultants who have taught everyone from undergraduate students to senior executives. We tailor hands-on training to your people’s roles, experience, and everyday work. We help them develop the skills and confidence to apply AI to real tasks and recognize where it can make a difference.

Engineering

Build AI that works in production.

Our engineering team includes Stanford graduates, an ARC Prize award winner, and a NeurIPS workshop author. Our team has built AI solutions in production at Toyota, Enbridge, and other enterprise clients. We build agentic AI and machine learning systems that connect to your data, work across your tools, and support your everyday operations.

Our team

Will Dick

Will Dick

TorontoCo-FounderEngineering Partner

Will is an engineer, founder, and professor with more than 15 years of experience in AI and machine learning. Before Don River, he founded and exited CVM Data Sciences, a machine learning consultancy that helped enterprise clients including Toyota and Verizon maximize marketing ROI. Previously, he was a quantitative analyst for a $30 billion real estate fund.

Will is a professor at Seneca Polytechnic. He holds a master’s degree from the University of Toronto and a graduate certificate in AI from Stanford. His autonomous AI agent placed second in the 2025 ARC-AGI-3 Preview Competition.

Yuri Petrov

Yuri Petrov

VancouverEngineering Partner

Yuri is an AI engineer who builds machine learning and agentic AI systems, with solutions in production at Toyota, Enbridge, and other enterprise clients. Before Don River, he worked alongside Don River founder Will Dick at CVM Data Sciences. He holds a master’s degree in computer science from Stanford University and a bachelor’s degree in computer science from the University of British Columbia.

Archit Tandon

Archit Tandon

HamiltonEngineering Partner

Archit is a data and machine learning engineer specializing in agentic AI and automation. He holds a bachelor’s degree in computer science from McMaster University, where he researched natural language processing and machine learning. He is a co-first author of a paper on multi-agent orchestration accepted to the NeurIPS 2026 Meta-Agents Workshop. His work focuses on turning advances in agentic AI into practical systems.

Momsad Khan

Momsad Khan

TorontoEngineering Partner

Momsad is a computer engineer with more than 15 years of experience delivering Salesforce implementations for enterprise clients. An expert in Agentforce and SI Force, he helps clients build AI tools and automation that connect with their existing systems and support everyday work.

Ian Bateman

Ian Bateman

TorontoCo-FounderStrategy Partner

Ian helps organizations put AI to work in everyday business processes. He has led AI automation initiatives across back-office operations and investment research, drawing on more than 15 years of experience in capital markets, investment management, and alternative investments. At Don River, he helps clients identify high-value opportunities for AI, rethink workflows, and turn AI capabilities into practical tools their teams can use.

Sara Ruwani

Sara Ruwani

TorontoStrategy Partner

Sara brings an evidence-driven approach to AI adoption, informed by more than a decade in public policy analysis and labour market research. At Don River, she focuses on understanding workflows, identifying opportunities for AI, and measuring results. She holds a master’s degree from the University of Cambridge and a bachelor’s degree from the University of Toronto.

Rohan Joseph

Rohan Joseph

TorontoStrategy Partner

Rohan brings more than a decade of experience in marketing, sales, and business development, including ten years leading business development at Purple Corps. At Don River, he helps clients identify where AI can support their growth and connect business needs with practical solutions.

Ensiyah Syed

Ensiyah Syed

TorontoStrategy Partner

Ensiyah helps organizations put AI to work where it truly makes a difference. With more than 5 years of experience in marketing, she designs automation workflows and AI agents for marketing and compliance teams. Her deep interest in psychology, anthropology, and human behaviour shapes how she builds: she starts with how people actually think and work, then designs tools that fit naturally into their day. A creative problem-solver at heart, she believes the best solutions use AI thoughtfully rather than in every process.

Let’s talk about your AI plans

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