clientelligent uses AI
to help you know your
We use machine learning to discover powerful insights into client behaviors and preferences that can elevate client engagement.
Our platform helps executives and sales professionals make smarter, data-driven decisions that can drive revenue growth, save money and keep your clients happy.
Clientelligent is trusted by some of the largest global financial services companies to deliver actionable client data-driven insight.
Client insight that has an impact.
The more you understand your clients, the better you can serve them. The better you serve your clients, the more your business can prosper.
We help companies better understand their clients by learning from their data. With machine learning, we can reveal new insights into your clients from the ever-growing amount of information available about their choices, then use these insights to predict and influence their next move.
Drive sales growth
Find the low hanging fruit that's easy to
pick but hard to spot
With machine learning, we can explore vast amounts of data to discover patterns and relationships that can shed new light on client preferences in a variety of circumstances.
We can use this insight to find out what products your clients are more likely to be interested in right now.
Be more efficient
Work smarter with data-driven leads
With data-driven leads and personalized product recommendations, sales teams can be more effective and more efficient with their resources.
We can also explore data to identify trendsetters. Targeting clients whose decisions influence their peers can have an exponential impact on sales.
Keep your clients
An ounce of prevention is worth a pound of cure
Don't wait for an exit interview to find out why a client is leaving. Data may be able to tell us why before they say goodbye.
Identifying potential client departures creates an opportunity to take preventative action.
Fuel successful product innovation
Find out what clients are really looking for
Innovation is one of the most powerful drivers of growth, but many new products fail.
Predictive analytics can help companies create more successful new products by delivering deeper insight into what clients are really looking for.
See where value is being created
Patterns in client transaction and engagement data can provide insight into the contribution your team members make and how effectively resources are being deployed.
Get unbiased insight
Bias can lead to missed opportunities
If left unchecked, bias can lead to sub-optimal decisions which can impede growth. Unbiased data analysis may reveal new insights that challenge our perceptions.
We collect data, build models and find patterns to discover new insights and predict outcomes. We build systems to manage massive data sets and experiment. We communicate by making complex things easy for everyone to understand and we commit to expanding the capabilities of our clients.
Based in Toronto and San Francisco, our team has a rich background in AI with experience at some of most innovative companies in the world and the skills to match. Our advisors are leaders in academia and business and provide us with perspective and expertise to help us help our clients succeed.
Clientelligent is incubated by the Fields Institute for Research in Mathematical Sciences Centre for Quantitative Analysis and Modelling (Fields CQAM) and is supported by MaRS Venture Services.
Bin Yu is a Chancellor’s Professor in the Departments of Statistics and Electrical Engineering & Computer Sciences at the University of California at Berkeley and a former chair of Statistics at UC Berkeley. Her research focuses on practice, algorithm, and theory of statistical machine learning and causal inference. She is engaged in interdisciplinary research with scientists from genomics, neuroscience, and precision medicine. Bin was a founding co-director of the Microsoft Research Asia (MSR) Lab at Peking University and is a member of the scientific advisory board at the Alan Turing Institute in the UK. She has been a consultant to several companies including Microsoft, eBay and GRAIL. Bin is a member of the U.S. National Academy of Sciences and Fellow of the American Academy of Arts and Sciences. She was a Guggenheim Fellow in 2006, and the Tukey Memorial Lecturer of the Bernoulli Society in 2012. She was President of IMS (Institute of Mathematical Statistics) in 2013-2014 and the Rietz Lecturer of IMS in 2016. She received the E. L. Scott Award from COPSS (Committee of Presidents of Statistical Societies) in 2018.
Neil is an active investor and has served on the boards of many private and public companies, including his current portfolio of businesses. He is the former President of Aston Hill Asset Management, having retired in December 2015. Neil has a strong track record of leadership and execution in the retail investment world. In late 2003 he founded Connor, Clark & Lunn Capital Markets Inc., where, as CEO and President, he raised over $2.5 billion in new assets before Aston Hill acquired the firm in 2013. Prior thereto, he was Executive Vice President and Portfolio Manager at AIC Group of Funds. Neil joined AIC in 1993 when the firm managed only $150 million in assets and was instrumental in its growth to over $15 billion as one of the three principals of the business. The funds he managed were the winners of numerous investment awards. In addition to his Bachelor of Commerce degree from McGill University, Mr. Murdoch also received a Bachelor of Law degree from the University of Toronto and a Master of Management degree from the Kellogg Graduate School of Management. He also holds the CFA designation. Mr. Murdoch is a member of the McGill Desautels International Advisory Board and a loyal supporter of the university. He is also active in the community, having co-founded Operation Guardian Force and having been a Governor at Appleby College and on the board of Gold Medal Plates.
Nathaniel graduated from Harvard University with a master's degree in applied mathematics and a bachelor's degree in computer science. He previously worked as a Data Scientist at Facebook, a Product Manager at Microsoft and a Software Engineer at Google. Before transitioning into the pure tech industry, Nathaniel gained experience as a quantitative analyst and trader at Goldman Sachs and Jane Street Capital. He is an avid reader and learner with an interest in educating. He teaches part-time at General Assembly in San Francisco and is developing open source teaching material for data science and machine learning.
President & Chief Scientist
Jamie is a Ph.D. graduate from the University of California, Berkeley where he conducted research at the intersection of data science and artificial intelligence. During his Ph.D, Jamie collaborated with leading researchers from Google Brain, Facebook AI Research (FAIR), Facebook Core Data Science and New York University. His research has been recognized by the prestigious Alexander Graham Bell scholarship (doctoral program) from the Canadian government and by a data science research award from Adobe. Jamie graduated from the University of Waterloo with highest honors, where he triple majored in statistics, pure mathematics, and combinatorics and optimization. Jamie also has experience in quantitative analysis and derivatives trading at Scotiabank.
Prior to co-founding Clientelligent, Darren was a financial services executive. He spent the majority of his career as a Partner and Director at Connor, Clark & Lunn Capital Markets Inc. (CC&LCM), a retail investment management subsidiary of Connor, Clark & Lunn Financial Group, one of Canada's largest asset managers. Darren held several senior leadership roles at CC&LCM, serving as CFO and later as President after a controlling interest in the company was sold to Aston Hill. As a portfolio manager, Darren managed quantitative and derivative-based strategies for CC&LCM and two Canadian banks. Prior to CC&LCM, Darren worked in Canada and the UK for a boutique investment management company. Darren has an MBA and a mathematics (operations research) degree from York University. He is also a CFA charterholder and a recipient of the Canadian Operations Research Society diploma.
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Toronto & San Francisco
30 Wellington Street West, 5th Floor
PO Box 129, Commerce Court
Toronto, ON M5L 1E2
artificial intelligence for client intelligence.
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