Our team designs and implements AI and machine learning solutions embedded in EPM and ERP platforms — from intelligent forecasting and anomaly detection to automated variance analysis and predictive planning.
“AI and machine learning in enterprise finance is only valuable when it is embedded in the systems finance teams already use — not in separate tools that require a data science team to operate. Our architects design ML solutions that work inside your EPM and ERP environment.”
Machine learning in FP&A is moving from experimental to operational. Organisations that integrate ML into their planning and reporting cycles are closing faster, forecasting more accurately, and spending less time on manual variance analysis. Our team helps enterprise finance functions make this transition.
We design ML solutions that are appropriate to the data environment and finance team capability. Not every organisation needs a sophisticated ML pipeline. Some need well-designed statistical models that improve forecast accuracy with minimal infrastructure. We scope the right solution for the actual problem.
AI governance is a critical and often neglected component of ML in finance. When a machine learning model influences a forecast or flags a variance, finance leadership needs to understand why — and be able to override it with confidence. Our architects design explainability and governance into every AI component we build.
Our team has implemented AI and ML components across Workday Adaptive Planning, Oracle EPM Cloud, and OneStream environments. We bring both the technical architecture expertise and the FP&A domain knowledge needed to make AI in finance actually work — not just in a proof of concept, but in production.
Ready to discuss your planning architecture?
Talk to our team →Our architects will assess your current environment and give you a clear, honest view of what needs to change.