EVIDENCE-BASED DATA SCIENCE

Causal AI/ML Causality-as-a-Service

CML Insight's mission is to help companies analyze and catalog causal insights to help organizations know what's working and what isn't so they can improve their outcomes. Causal AI is a step forward from Predictive AI and answers many questions beyond basic risk predictions.

We have over twenty years of experience bringing Predictive and Causal AI to Healthcare, Defense, Education, and Fintech.

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What is Causal AI/ML?

Causal AI/ML identifies the underlying web of causes of a behavior or event and furnishes critical insights that correlational models cannot do. 

Causality
INDUSTRIES

Use-Cases

CS

Customer Success

How do we predict customer churn? What activities and actions improve our chances to increase renewals and reduce attrition? How do we measure successful strategies and build an evidence-based catalog of actions to help train future CS and Sales professionals?

edu

Education

What supports and interventions drive student success outcomes? How do we quantify the impact? What edtech products really work and demonstrate evidence of efficacy. How do we improve the cycle of student from lead to application to enrollment to graduation?

HR

Human Capital

How do we find & recruit the best employees? What Learning & Development resources are paying off? What investments help us retain employees? What actions help us with workplace safety?

fintech

Fintech

How do we know which activities lead to higher CLTV and client satisfaction? How do we predict churn, when should we intervene and how? What strategies help our clients achieve the financial outcomes they desire in a timely way?

health

Healthcare

What treatments, nudges, and interventions drive better patient results? What combination of treatments help patients struggling with chronic disease. How do we optimize our portfolio of limited resources to drive the greatest return on patient outcomes?

SaaS

Evidence HubTM

zBoth
METHOD

Create impact with real data

CML Insight is a full cycle advanced data science consulting and software company. We kickstart and augment your AI analytics teams' work.

We built CML to help level-up an organization's AI/ML strategy through custom predictive and causal modeling to measure impact and efficacy of initiatives and products. 

We are the go-to company for CEOs, COOs, CHROs, CLOs, and Chief Analytics Officers who want to generate critical insights and continuously improve on their critical KPIs. 

Causation Triangle
SOLUTIONS

Benefits

playbook

Build an Evidence Catalog

Build a quantifiable evidence-based database that can supercharge your corporate Knowledge Management systems.

automation

Scale & Automate AI/ML

Launch continuous production models in a matter of weeks for decision making with rigorous validation and accuracy.

predictive

Initiate Predictive Analytics

Generate key actionable insights based on what is likely to happen with customers, agents, students, patients, or staff.

causal

Discover Causal Analytics

Receive advanced prescriptive (causal) insights into what actions are leading to successful outcomes and how impact potential they have.

lifecyc

Generate Lifecycle Insights

Visualize key momentum points, interventions, actions that lead to success or LTV for students, customers, or patients.

EBOOK

Get our free ebook on the Causal AI/ML revolution in Education

Get our free ebook on how Causal AI/ML will improve the education sector

PEOPLE

Meet Our Team

CEO / Founder

David Kil

Dave has over thirty years of experience leading data science teams and pushing the frontiers of predictive and causal analytics. A former Chief Data Scientist at Humana and Civitas Learning, Dave is a thought leader in Healthcare, Education, and the Financial sector.

CTO / Co-founder

Daya Wimalasuriya

Daya has worked both in academia and the software industry including stints as a college professor and a principal data scientist. Daya obtained his Ph.D. from the Department of Computer and Information Science at the University of Oregon.

Chief Growth Officer / Co-founder

Rupal Shah

Rupal is a high growth start-up operator with over twenty-five years of experience as a consultant and sales leader. He has held senior positions at start-ups backed by Andreessen Horowitz, Emergence Capital, Goldman Sachs and many impact investors.

Reading

Publications

Research

ASU: Catalyzing a Culture of Care and Innovation Through Prescriptive and Impact Analytics To Create Full-Cycle Learning

Article

Stanford Social Innovation Review: The Case for Causal AI

Research

Educause: Preventing a Winter of Disillusionment: Artificial Intelligence and Human Intelligence in Student Success

Research

Educause: Why Data Matters for Student Success in a Post-Pandemic World