Most AI projects fail on the data, not the model. Having spent twenty-five years on the engineering side, we tend to know within a week whether the data you have can support the question you are asking - and we would rather tell you then than after a six-month pilot.
We build predictive and classification models on business data, and we are equally willing to tell you when a well-specified report would answer the question at a fraction of the cost.
What this includes
- Regression, classification and predictive modelling
- Demand forecasting and capacity-versus-demand analysis
- Customer churn, attrition and win-back modelling
- Neural networks in TensorFlow
- Sentiment analysis on unstructured text
- Graph analysis and Neo4j
- Python - Pandas, NumPy, scikit-learn, Matplotlib
- Honest assessment of whether your data can support the question
What you end up with: A model in production that people act on, or an early and well-argued answer that you do not need one.
Every engagement includes detailed documentation of our findings, and all source code and artefacts for any bespoke product - documented for your teams to maintain and understand. We maintain a strict level of confidentiality throughout.