Custom-tailored optimization
Slingshot's ML models are automatically fine-tuned on your workloads for data-driven modeling that result in high-impact optimizations.
Self-improving optimization
Slingshot uses closed-loop feedback to continuously improve its recommendations based on the impact of the previous ones.
Variable-sized data
A closed feedback loop enables ML models to adapt to changes, like data size growth or cost anomalies, before they impact the business.
Any workload
Our ML models can automatically train on any workload, including ETL jobs, LLM jobs, ML jobs, periodic jobs, large jobs and short jobs.
Additional features