Artificial Intelligence & Machine Learning

Glean greater insight

Glean greater insight from your structured and unstructured data. Our consultants will leverage AI and machine learning techniques for Pattern Recognition, Classification & Regression, Decision Trees, Clustering, Natural Language Processing

Unique mix of skills

Our team offers a unique mix of actuarial, data science and AI engineering expertise offering end-to-end Artificial Intelligence (AI) and Machine Learning (ML) solutions tailored to your business goals. Whether youre just starting to explore AI or looking to scale existing initiatives, we can help identify the most impactful AI use cases, design data strategies, and build scalable machine learning models that drive real-world results.

How we work

We begin with a short "free of charge" engagement exploring objectives, data infrastructure, workflows, and analtytic opportunities. From there, we hold a workshop to explore the art of the possible and how Proteus AI can help. Common topics include data preparation, model training, evaluation, and deployment scenarios ensuring solutions are accurate, explainable, and aligned with your objectives. Our actuarial background brings valuable "real world" insight over traditional "AI Only" solutions

AI Workflows

In addition to development, we offer support for MLOps, helping clients operationalize their AI workflows for continuous improvement, monitoring, and governance. Our consultants bring domain expertiseto guide ethical, compliant, and effective AI adoption. With a focus on long-term value and measurable ROI, we partner with clients to turn AI potential into business performance

Consulting Flexiblity

AIML algorithms can sometimes be more an art than a science and hence our projects are phased to allow easy handover at any stage should requirements change or outcomes are determine early. We are more than happy to work as part of your existing team, or work on a more independent basis.

Financial Datasets

We have experience working with financial datasets for both supervised and unspervised models. Recent case studies include retail debt recovery propensity and portfolio pricing. It is very important with high dimensionality financial datasets to determine the key features that drive the model. We can help you identify these features and build a model that is both accurate and interpretable. We can also help you understand the impact of different features on the model output and how to use this information to make better business decisions.