Services
Applied Science, End to End
From problem formulation to production deployment — rigorous methods applied at industry speed.
Mathematical Optimization
Hard Allocation Problems
Routing, scheduling, resource allocation, supply chain — combinatorial and multi-objective problems where standard tools fall short and the solution structure matters.
Scheduling & Resource Allocation
Staff scheduling, machine assignment, fleet dispatch, warehouse slotting. We formulate the problem precisely, choose the right algorithm for the structure, and deliver a system your team can operate and adjust.
Multi-Objective Optimization
Problems with competing objectives — cost vs. service level, throughput vs. quality — require understanding the trade-off structure, not collapsing it to a single metric. We map the solution frontier and build tools that let decision-makers navigate it. Creator of pymoo, the most widely used Python framework for multi-objective optimization.
Operations Research & Routing
Vehicle routing, job-shop scheduling, facility location, supply chain flow. Classical OR formulations combined with modern metaheuristics, matched to the problem size and operational constraints at hand.
Algorithm Design
Custom algorithm development for problems where standard solvers do not fit the structure. When the problem requires something built from first principles rather than configured from a library.
Machine Learning
Production ML Systems
Custom model development from the right statistical foundation — through validation, deployment, and the infrastructure your team needs to maintain it.
Custom Model Development
Forecasting, ranking, classification, anomaly detection. The model choice follows the data structure and the decision it needs to support — validated against the right metrics for how it will actually be used.
Causal Inference
Experiment design, observational study methods, uplift modeling. For decisions where correlation is not enough and you need to understand what is actually causing what.
MLOps & Production Pipelines
Training, evaluation, and serving infrastructure built to run reliably in production. Includes documentation and a handoff session so your team can maintain and extend the system independently.
Experimentation & A/B Testing
Experiment design, power analysis, and statistical evaluation for product and business decisions. Getting the methodology right before running the test, not after.
AI Systems
LLM-Powered Workflows
Language models applied to specific operational problems — document processing, structured extraction, decision support — with evaluation and observability built in.
LLM Integration
End-to-end language model pipelines for a defined operational task: extraction, classification, summarization, code generation. Scoped to a concrete problem with explicit evaluation criteria.
Retrieval-Augmented Systems
Search and question-answering over your data. RAG pipelines designed with the right chunking strategy, embedding model, and retrieval evaluation for the use case.
Agentic Workflows
Multi-step AI systems that automate complex operational processes. Built with defined tool boundaries, fallback behavior, and human-in-the-loop controls where appropriate.
Evaluation & Monitoring
The measurement layer for language model systems — evals, logging, and production monitoring. Necessary for knowing whether a system is working and for improving it over time.
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