Capabilities
Capabilities built for decisions.
Each pillar stands on its own, each grounded in the same doctoral rigor and executive fluency. Engage us for a single capability or a portfolio of them.
Data Science and Machine Learning
We build across the full spectrum of analytics and machine learning, descriptive, diagnostic, predictive, and prescriptive, scoped to decision impact. That includes forecasting, natural language processing, and computer vision, grounded in statistical rigor: time series, experimentation, and uncertainty quantification, carried from model development through deployment. Toolset depth includes Python, R, SQL, SAS, MATLAB, Spark and Databricks, and cloud platforms including AWS and Google Cloud.
Full detailWhen to engage us
- Forecasting or workforce modeling needs statistical rigor, not a black box.
- A machine learning, NLP, or computer vision solution needs to be explainable to executives, not just accurate.
- Uncertainty quantification matters because the decision is expensive to get wrong.
- Models need a path from prototype to production, not a notebook that never ships.
Operations Research and Optimization
We build mathematical models for resource allocation, scheduling, logistics, and investment planning, backed by doctoral research and peer-reviewed publication. That includes simulation and simulation-optimization for capital and portfolio decisions, metaheuristics and large-scale optimization such as tabu search, GRASP, dynamic programming, and Markov models, and rigorous economic and cost-benefit analysis.
Full detailWhen to engage us
- A resource allocation or scheduling problem has too many variables for intuition alone.
- Capital or portfolio decisions need simulation-optimization, not a static spreadsheet.
- Large-scale planning requires metaheuristics beyond standard solvers.
- Leadership needs an economic and cost-benefit case that will hold up under scrutiny.
Analytics Strategy and Decision Science
We build enterprise analytics strategy, operating models, and governance, then translate the output into executive decision support: distilling complexity into decision-ready products rather than dashboards no one opens. This includes building analytics organizations, communities of practice, and data governance bodies, plus direct analytics talent development and technical mentorship.
Full detailWhen to engage us
- Analytics exists across the organization, but no operating model or governance ties it together.
- Executives need decision-ready products, not another dashboard no one opens.
- You are building an analytics organization, a community of practice, or a governance body from scratch.
- Your analytics talent needs technical mentorship to reach the next level.
AI Security and Assurance
We assess and assure AI systems before they fail in public. That includes AI risk assessment, red-teaming concepts and model assurance, governance for safe deployment in regulated and mission-critical environments, and data protection and responsible-use policy that legal teams can stand behind.
Full detailWhen to engage us
- An AI system will inform decisions with legal, financial, or safety consequences.
- Regulators or auditors are asking questions your team cannot yet answer.
- You need a risk assessment and assurance review before deployment, not after an incident.
- Data protection and responsible-use policy have not kept pace with your AI ambitions.
Generative AI and AI Agents
We take generative AI from use-case discovery through evaluation and deployment strategy. That includes agentic workflow and automation design, retrieval-augmented generation over enterprise knowledge, build-vs-buy and vendor evaluation, and human-in-the-loop design wherever a decision carries real consequence.
Full detailWhen to engage us
- You need to separate genuine LLM use cases from expensive experiments.
- You are evaluating agentic automation and need an honest build-vs-buy assessment.
- A retrieval-augmented generation system needs to be trustworthy enough for real decisions.
- High-stakes workflows require human-in-the-loop design, not full automation by default.
AI Strategy and Governance
We build enterprise AI strategy, roadmaps, and operating models grounded in your actual constraints. That includes responsible AI and governance frameworks, honest readiness and maturity assessment, and direct advising for executives and boards on AI adoption and digital transformation. Every recommendation ties back to a measurable business outcome.
Full detailWhen to engage us
- Leadership needs a defensible AI roadmap, not a slide deck of buzzwords.
- The board is asking for an AI governance framework and no one owns the answer.
- Multiple pilots exist. None has scaled, and it is unclear why.
- You need a readiness and maturity assessment before committing new investment.