Enterprise Causal AI/ML.

Moving beyond predictions. 

Using Real-World Evidence to Measure & Improve KPIs

Causal AI / ML is one of the most exciting new advancements in analytics. CML Insight helps organizations measure and improve their critical KPIs

We work with educational institutions, government, edtech companies, fintech and healthcare providers to discover the incredible insights that remain hidden in data.

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What is CML Insight?

CML Insight is an advanced data science product and services company designed to help e organizations measure the impact and efficacy of their initiatives, programs and products to improve outcomes. Using advances in Causal AI/ML our highly experienced data scientists and machine learning experts leverage novel approaches to uncover the causal relationships in your data.

We provide insights using your historical information, and more importantly we help you run experiments to continuously improve the organization against critical KPIs. 


Our Approach

We develop an initial set of insights using your historical data set. We then focus on your KPIs, the ones you are trying to improve and have the highest effect on solving your operational problems or student success challenges. We provide specific evidence-based recommendations so you don’t have to guess and we track the efficacy of those experiments over time.

Using Causal ML, we leverage a defined set of complementary ML algorithms with a focus on improving business KPIs or student success, not just on predicting risk. 

Portfolio Optimization

CML Insight delivers a specific map of your initiatives, interventions, investments ranked to better understand which streams of work have the highest impact potential. This allows you and your support team to better optimize your portfolio of work to serve your diverse students and users. We also help you run play-based experiments over time to continually refine and improve the efficacy of your interventions and products to maximize outcomes. 

Intervention Scatter Plot

Recent Blog Articles

For Far Too Long...
Predictions alone do not lead to student success outcomes August 2022
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The Causal AI/ML Revolution in Education
Fall 2022 eBook October 2022
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Lowering student equity gaps through analytics
The downside risks of improperly using ML November 2022
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A Conversation with Dave Kil
Trustworthy ML/AI in Higher Education December 2022
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Published Research & Causal AI / ML Articles

“Where causation is concerned, a grain of wise subjectivity tells us more about the real world than any amount of objectivity.”

Judea Pearl, The Book of Why: The New Science of Cause and Effect

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Stanford Social Innovation Review
The Case for Causal AI
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Gartner 2022
Use Causal AI to Go Beyond Correlation-Based Prediction
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Educause 2021
Artificial Intelligence and Human Intelligence in Student Success
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Educause 2021
Why Data Matters for Student Success in a Post-Pandemic World
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2021 Nobel Award
Natural experiments help answer important questions for society
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Creating impact using Real-World Evidence (RWE)

New advances in Causal AI / ML allows us to go beyond basic  “pattern-matching” and “curve fitting” typically used over the past decade via predictive analytics.

Causal AI / ML gives us the ability to learn cause-and-effect relationships; the capability to simulate and measure impact of interventions; and allows us the ability to imagine what-ifs beyond the limits of historical data. 


I founded CML Insight to democratize machine learning insights to help all organizations improve the way they operate and drive meaningful outcomes.

Dave Kil
Founder of CML Insight

Ready to use Causal AI & ML?

Get started today by speaking with one of our specialists