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ESP is a leader in carbon and utility management software, on a mission to embed sustainability into every business’s performance. They have large clients in the multi-site retail, commercial property, government, and industrial sectors.

Jeremy Allen, ESP’s founder and CPO, approached Arcanum to support the up-scaling of ESP’s data science and machine learning (ML) capability.

They had already started on the journey, embedding ML into a core IoT-related service, but needed a partner to build out an industrial-scale MLOps function and support the ongoing performance management.



Review: The Arcanum team of data scientists and MLOps engineers reviewed the existing architecture, pipeline and algorithms.
Migrate: We migrated the whole ML infrastructure from the existing fixed deployment architecture to our scalable, flexible and resilient infrastructure as code set up.
Validate: Validation of the model accuracy and performance on the new setup was established as a benchmark for future measurement.
Monitor: Once live, the Arcanum monitoring capability provides ESP with a single view of infrastructure and ML performance; a view that stakeholders did not have before.
Manage: Running as a managed service, the Arcanum team are responsible for improving the ML accuracy over time; training and deploying the models via the Accelerate Platform.