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Decrease in model development time


Experiments run in parallel

SymphonyRM Produces Breakthrough ML Models by Accelerating R&D with Prefect Cloud

Prefect Cloud's workflow semantics, centralized platform, and advanced infrastructure integrations allowed SymphonyRM to accelerate R&D by automating model updates and retraining while reducing time to develop and maintenance.

As a vendor to covered entities under HIPAA, security and compliance are huge issues for us. Prefect’s hybrid execution model was key to being able to run with Cloud while none of our client data left our infrastructure.

Joe Schmid

CTO | SymphonyRM

By cutting our machine learning experiment time from 2 days to 30 minutes we had a huge gain in the number of experiments we could run each day. By allowing us to iterate faster, we could quickly experiment with more machine learning approaches, which ultimately got us to production ready models very quickly.

Joe Schmid

CTO | SymphonyRM

I used the parallelized hyper-parameter tuning (incredible) to run about 350 experiments in 30 minutes, which normally would have taken 2 days.

Andrew Waterman

Data Scientist | SymphonyRM