Services

Reproducible Pipelines

We specialize in creating and implementing reproducible data pipelines to transform your raw data into reliable, ready-to-use assets. A reproducible pipeline ensures that your analyses and reports are not only accurate today but can also be recreated perfectly in the future, regardless of who runs them or when.

Our services help you build a robust data infrastructure that saves time, reduces errors, and boosts confidence in your data-driven decisions. We focus on four key areas:

Automation: We automate data cleaning, transformation, and analysis processes, moving your team away from manual, error-prone tasks.
Version Control: We use version control systems to track every change to your code and data, making it easy to see the history of your work and revert to previous versions if needed.
Documentation: We create clear, comprehensive documentation for your data and code, ensuring that your pipelines are understandable and maintainable for anyone on your team.
Scalability: We design pipelines that can handle growing data volumes and complexity, so your infrastructure can evolve with your business.

Causal Inference

We provide causal inference and design consulting to help you move beyond simple correlation and establish what truly drives your outcomes. Understanding causality is crucial for making effective, evidence-based decisions, whether you’re evaluating a new marketing campaign, a public health intervention, or a product feature.

Our services focus on helping you design studies and analyze data in a way that isolates the effect of your interventions. We specialize in a range of techniques, including:

Experimental Design (A/B Testing): We help you design and analyze controlled experiments to rigorously test the impact of your interventions.
Quasi-Experimental Methods: When controlled experiments aren’t feasible, we use sophisticated statistical methods like difference-in-differences, instrumental variables, and regression discontinuity to approximate a causal effect.
Observational Causal Inference: We employ techniques such as propensity score matching and structural equation modeling to draw causal conclusions from existing observational data, helping you uncover relationships without needing to run a new experiment.

Causal Inference | Interrupted Time Series | Regression Discontinuity | Propensity Scores

Statistical Software Development

We develop statistical software in R and Python to help you build custom tools that are efficient, reliable, and tailored to your specific analytical needs. Our services are ideal for organizations looking to create reusable functions, automate complex workflows, or productize statistical models.

Our expertise includes:

R Package Development: We create professional-grade R packages for your analytical team. This allows you to consolidate your code, share custom functions easily, and ensure consistent application of statistical methods across projects.
Python Library Development: We build robust Python libraries for data manipulation, statistical modeling, and machine learning. We focus on writing clean, well-documented code that integrates seamlessly with your existing systems.
Workflow Automation: We design and implement scripts and applications that automate repetitive statistical tasks, from data cleaning and report generation to model training and deployment.
API and Web Application Development: We can wrap your statistical models and algorithms into a user-friendly API or a web application, making your advanced analytics accessible to a wider audience, including non-technical stakeholders.

R | Python | Package Development | Automation | Documentation

Machine Learning

We offer consulting for developing machine learning models to help you turn your data into predictive and analytical assets. Our services are designed to guide you through the entire machine learning lifecycle, from initial data exploration to model deployment and monitoring, ensuring that your models provide real, measurable value.

Our approach focuses on building robust and explainable models that drive better decision-making. We specialize in:

Predictive Modeling: We build models that forecast future outcomes, such as customer churn, sales trends, or asset failure. This allows you to anticipate events and take proactive measures.
Classification: We create models that categorize data, such as identifying fraudulent transactions, sorting customer feedback, or classifying medical images.
Natural Language Processing (NLP): We develop models that understand and process human language. This includes sentiment analysis, topic modeling, and building conversational AI.

Evidence Synthesis

We specialize in evidence synthesis to help you make informed decisions. Our services go beyond a simple literature review; we systematically collect, evaluate, and combine research findings to provide clear, actionable insights.

Whether you’re developing a new product, shaping a policy, or advancing a scientific field, our rigorous approach helps you understand the current landscape of evidence, identify gaps in research, and confidently move forward.

Our expertise includes:

Systematic Reviews: We conduct comprehensive reviews of existing research to answer specific questions with the highest level of scientific rigor.
Meta-Analysis: When appropriate, we use statistical methods to combine data from multiple studies, providing a more precise and powerful conclusion.
Scoping Reviews: We map the available evidence on a topic to help you determine the feasibility of a larger project and identify key concepts and research areas.

Research Synthesis | Meta-Analysis | Literature Review | Scoping Review | Systematic Review

AI / LLM Model Creation & Support

AI has incredible potential to transform how organizations work, from automating repetitive tasks to uncovering patterns that would be nearly impossible to find manually. However, with numerous tools and platforms available, it’s not always clear where to begin or whether a fully customized solution is necessary.

Our AI and large language model (LLM) services empower you to navigate this evolving space with confidence. We focus on building solutions that are not only technically sound but also practical, ethical, and aligned with your goals. That means taking a human-in-the-loop approach, where people remain at the center of decision-making, supported, not replaced, by AI.

Our services include:

AI Strategy and Assessment: Evaluate your current workflows to identify opportunities for AI integration, including determining whether existing tools are sufficient or if custom development is required.
Custom LLM Development: Build tailored language models for specialized tasks like document summarization, knowledge base search, or domain-specific conversational agents.
Human-in-the-Loop Design: Create systems where AI augments human expertise, with clear feedback loops and oversight to ensure accuracy, trust, and ethical use.
Evaluation and Optimization: Benchmark and refine models to maximize performance while reducing bias and maintaining explainability.

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