Turning the data you already have into decisions you can defend.
TwinSight is a research and consulting practice led by Matthew Sazma, PhD. We apply causal inferential statistics — a newer approach that separates cause from correlation — to help organizations understand what's actually driving their outcomes.
First place — Data to Decision Challenge.
TwinSight won the top prize in the Griffiss Institute's Data to Decision Challenge, a competition to turn complex digital-twin data into intelligent, real-world decisions. Competing against teams from research institutions and industry, the entry was recognized for its rigorous approach to causal inference and its emphasis on keeping human judgment central to every decision.
Research rigor applied to real decisions.
We're not a data dashboard firm or an AI vendor. We're researchers who know how to work with messy, real-world data and produce conclusions an organization can actually act on.
Causal analysis
We identify what's actually driving an outcome — separating cause from the many things that merely correlate with it.
Evidence synthesis
We assemble and weigh evidence across sources, producing conclusions that hold up to scrutiny.
Decision framing
We help define what question is actually being asked — the hypothesis behind the ask, the constraints, and who's affected.
Scenario analysis
We reason through how outcomes would likely shift under different interventions, before any commitment is made.
Translation
We turn rigorous findings into clear, defensible guidance — without requiring a statistics background to understand them.
Advisory
We work alongside existing teams and experts, supplementing their judgment with evidence rather than replacing it.
Every engagement runs like a study.
Disciplined, auditable, and built around the actual decision — not the available data.
Frame
Get the real question right. The hypothesis behind the ask, the constraints, and what a good answer actually looks like.
Analyze
Apply causal inference to existing data. No new infrastructure needed — we work with what you already collect.
Validate
Test against history. Quantify confidence. Report what the evidence can't yet explain.
Deliver
Clear, defensible guidance your team can act on — with the reasoning fully auditable.
Supplementing, not replacing. The evidence informs the decision — the human makes it. That's not a caveat; it's the philosophy that earned us the top prize.
Cross-disciplinary, by design.
Causal inference at the scale of real-world decisions requires more than one kind of expertise. The TwinSight team brings together statistics, cognitive science, engineering, and sensing — with all of it pointed at the same goal.
Matthew A. Sazma, PhD
PhD, UC Davis; MA, University of Chicago. Former assistant professor with published research on cognition, stress, and memory. Taught research methods, statistics, and cognitive psychology. Leads TwinSight's research direction and consulting engagements.
Alyssa Borders, PhD
15+ years in data analysis and visualization, including large HIPAA-compliant government databases at California's HCAI.
Erik W. Ness
Full-stack developer for a $1B+ auto group. Built the MEVN reporting framework and real-time data pipelines used across dozens of locations.
Matt L. Miller, PhD
Assistant Professor of Psychology, Oakland University. Expertise in simulation, modeling, and municipal data-to-action research.
We'd be glad to connect.
Whether you're working on a data-intensive decision, exploring a research collaboration, or just want to understand more about causal inference — reach out. No pitch, no pressure.
Within two business days
Minnesota, United States