Selected team experience
Understand how your customers behave and what to do about it.
Build AI deployments that stay current and work with your employees.
Vendor-neutral advisors. A small number of clients at a time.
We build models to interpret your data: customer segmentation, churn prediction, lifetime value. You get named segments and quantified revenue exposure.
Which customers will change behaviour if you act? We build models that direct intervention to where it produces measurable value.
Measure incrementality so spend follows evidence. Adaptive A/B testing so you know which workflows work best and for whom.
How do you know whether AI is helping? We design evaluation frameworks that measure productivity, quality, reliability, safety, and return on investment. Avoid deployments that fail to deliver business value.
We review your workflow and data to identify where AI can improve productivity, reduce costs, or improve decision-making. We deliver a prioritized roadmap of opportunities, expected ROI, implementation complexity, and risk.
We design and evaluate your AI pilot project: workflow design, human oversight procedures, success metrics, vendor evaluation, and deployment planning.
Scoped analysis or evaluation with a defined deliverable and timeline. Decisions in weeks.
Half-day to full-day sessions for leadership teams on AI capabilities and human-AI workflow design. Research-grounded, vendor-neutral, tailored to your use cases. View workshops →
A senior scientist embedded in your organization at a fixed fraction of full-time. We own your AI evaluation agenda, vendor decisions, and analytics roadmap: you get an executive hire without the search or the salary. Limited to a small number of concurrent clients.
Our core team is supported by affiliated experts across the University of Toronto and the Vector Institute.
AI researcher. Cognitive scientist. University of Waterloo | MIT. Holds several NeurIPS paper awards and AI patents. Studies how intelligent systems - human and machine - reason, plan, and learn. Applies that thinking to consulting in data systems, AI design, safety and adoption, behavioural modelling, and strategy.
Deep learning researcher. PhD supervised by Nobel laureate Geoffrey Hinton. Research Scientist, Google Brain. Canada CIFAR AI Chair, Vector Institute. Research and consulting across medicine, finance, education, oceans, and creative sectors. Award-winning musician.
Human-Computer Interaction, Statistics, & AI researcher. Berkeley/Stanford/Harvard|University of Toronto. Uses Adaptive A/B Experimentation and human-computer interaction to help organizations discover when AI does and doesn't work – and adapt to different contexts. Won $1M XPRIZE for the future of AI based Experimentation.