Designed to meet your particular modeling needs
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Earn a Return on AI & ML
The most advanced Optimization Engine that delivers better results, faster and cheaper, than all standard tuning methods
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Tune Any Model
Black-box optimization that efficiently optimizes any machine learning, deep learning, artificial intelligence, simulation, or other model of your choosing
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Retain Flexibility
Our API-enabled solution easily plugs into any model management platform or model development framework so you retain flexibility in your technology stack
Select the right optimization approach for you
Grid Search | Random Search | Open Source | ||
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Models | ||||
1-4 Parameters | ||||
5-10 Parameters | ||||
11-100 Parameters | ||||
Any Model Type | ||||
Ease of Use | ||||
Low Maintenance | ||||
Reliability at scale | ||||
Organizational control | ||||
Experiment analysis | ||||
API-enabled | ||||
Priorities | ||||
Performance | ||||
Expert productivity | ||||
Compute utilization | ||||
Wall-clock efficiency | ||||
Variety of use cases | ||||
Competing objectives | ||||
Constraints | ||||
Conditional parameters | ||||
Long training cycles |
Proven Results
By optimizing each model, teams who invest in automated hyperparameter optimization will amplify the performance and impact of models on their business. SigOpt’s customers also typically realize higher performance from models tuned with our solution, and, in certain cases, use SigOpt to solve challenges that unlock entirely new business opportunity.
Accelerate Wall-Clock Time to Tune
Learn More About Our Optimization Approach
Optimization is in our DNA. SigOpt was founded by the creator of the Metric Optimization Engine (MOE) and our research team has spent years building and refining our ensemble of applied optimization algorithms to scale with our enterprise customers’ needs. Built by experts for experts, we have a deep appreciation for the broader research community from which we draw inspiration and to which we regularly contribute.
