We build and apply computational models to help organizations understand complex systems — from environmental risk and climate impact to economic forecasting and market dynamics. Our work combines deep quantitative expertise with practical domain knowledge to produce actionable insights.
Our modeling practice integrates expertise in financial engineering, applied mathematics, and large-scale data analysis. Whether the challenge is simulating regulatory impact, modeling supply chain risk, or quantifying environmental exposure, we deliver rigorous, defensible analysis.
Quantitative Rigor, Practical Results
Our computational modeling practice is grounded in published research and real-world application across financial markets, environmental systems, and complex regulatory environments. We combine academic rigor with engineering pragmatism to deliver models that are not just theoretically sound but operationally useful.
From Data to Defensible Decisions
What We Offer
Environmental Modeling
Climate risk, emissions modeling, and environmental impact simulation.
Economic & Financial Modeling
Market dynamics, regulatory impact analysis, and quantitative forecasting.
Agent-Based Simulation
Complex systems modeling using agent-based and Monte Carlo simulation techniques.
Risk Quantification
Probabilistic modeling of operational, financial, and environmental risk.
Scenario Analysis
Multi-scenario planning and stress testing for strategic decisions.
Data Pipeline Development
End-to-end data infrastructure for model inputs, calibration, and reporting.
Selected Projects
Predicting Supreme Court Decisions
General predictive model achieving 70.2% accuracy across 240,000+ justice votes, published in PLOS ONE (2017).
Measuring the Complexity of the U.S. Code
Mathematical analysis of the structure and complexity of federal law, published in Artificial Intelligence and Law (2014).
Measuring the U.S. Regulatory Ecosystem
Large-scale modeling of the regulatory landscape, published in Journal of Statistical Physics (2017).
Law on the Market
Evaluating the securities market impact of 211 Supreme Court decisions (2015).
Domain-Specific NLP Tooling
Custom BPE tokenizers and NLP pipelines optimized for legal and financial text, delivering significant accuracy improvements over general-purpose models.
How We Engage
Frequently Asked Questions
- What types of environmental modeling do you do?
- We build models for climate risk assessment, emissions forecasting, environmental impact simulation, and natural resource analysis. Our models help organizations quantify exposure, plan mitigation strategies, and meet regulatory reporting requirements. We work with both proprietary and public datasets to calibrate models to real-world conditions.
- How does economic modeling support decision-making?
- Our economic models help organizations understand market dynamics, forecast demand, quantify regulatory impact, and evaluate strategic alternatives. We use techniques ranging from econometric analysis to agent-based simulation, depending on the complexity of the system and the decisions at stake.
- What is agent-based simulation?
- Agent-based simulation models complex systems by representing individual actors (agents) with their own behaviors and decision rules. As agents interact, emergent system-level patterns arise that traditional equation-based models may miss. This approach is particularly valuable for modeling markets, supply chains, regulatory ecosystems, and environmental systems where heterogeneous actors interact in non-linear ways.
- What technical capabilities does your team bring?
- Our modeling practice draws on advanced training in financial engineering and applied mathematics, with fluency across modern quantitative computing environments and large-scale data infrastructure. Our work spans financial markets, environmental systems, regulatory ecosystems, and AI evaluation — with an emphasis on reproducibility, defensibility, and practical utility.
Related Services
Related Insights
An independent evidence review of Oracle's $43.1 billion tax abatement application under Michigan Public Act 198: the statutory six-month commencement rule, the county's own permit record, the consent judgment, principal findings, and recommended actions — revised July 18, 2026 after the Township Board's July 14 and July 17 votes, with the full 46-page report available for download.
The Proposed ITC Oneida–Sabine Lake 345 kV Transmission LineAn independent, reproducible route and environmental analysis of ITC's seven published alternatives for the Oneida–Sabine Lake 345 kV line in central Michigan — scored on the Act 30 factors with and without House Bill 5940's freeway credit, stress-tested across a million weightings, and resolved township by township. Revised September 2026; full 41-page report and explainer video.
Independent Traffic & Siting Analysis of the Proposed Chicago Bears StadiumA public-data traffic analysis of the proposed Bears stadium at Arlington Park: roughly 32,000 game-day vehicle trips, 112 local-street bottlenecks that persist in every mode-share scenario, the Metra surge-service gap, and equity concentration on the impact corridors — with five adoptable recommendations. Full 55-page report available for download.
Predicting the Supreme Court: AI Meets Legal OutcomesHow our machine learning research achieved breakthrough results in predicting Supreme Court decisions, and what it means for the future of legal AI.