Why Optimize?
Your researchers are your most valuable machine learning asset and will be responsible for developing the differentiated models that create the most value for your business. And experts who automate hyperparameter optimization develop high-performing models at a faster rate. Maximize the productivity of your experts with SigOpt’s black-box optimization solution and realize the full potential of your machine learning investment.
Growing pressure to deliver AI results
As AI expectations soar, so does the pressure on companies to realize economic value from their machine learning investments. This pressure places a premium on researchers capable of developing differentiated models for each particular business need. Performance often determines whether these differentiated models make it into production, and model optimization often plays a significant role in this process.
AI threatens to disrupt industries
Competition from AI-first companies compounds the pressure on executives to realize this AI impact on an even faster timeline. Modeling is the next wave of innovation that threatens to “eat the world” and reshape trillion-dollar industries in the process. Without investment in researchers and tools that augment them, incumbents risk losing to new entrants who do.
Improving productivity is at a premium
Although the supply of machine learning engineers is exploding, it still cannot keep pace with demand. This puts pressure on companies to augment each of their researchers as much as possible to realize their full machine learning potential. To attract and retain this level of talent, teams are investing in best-in-class tools so they have the best possible research environment. And they are automating key parts of the process like model optimization so their teams are as productive as possible.
Growing pressure to deliver AI results
As AI expectations soar, so does the pressure on companies to realize economic value from their machine learning investments. This pressure places a premium on researchers capable of developing differentiated models for each particular business need. Performance often determines whether these differentiated models make it into production, and model optimization often plays a significant role in this process.
AI threatens to disrupt industries
Competition from AI-first companies compounds the pressure on executives to realize this AI impact on an even faster timeline. Modeling is the next wave of innovation that threatens to “eat the world” and reshape trillion-dollar industries in the process. Without investment in researchers and tools that augment them, incumbents risk losing to new entrants who do.
Improving productivity is at a premium
Although the supply of machine learning engineers is exploding, it still cannot keep pace with demand. This puts pressure on companies to augment each of their researchers as much as possible to realize their full machine learning potential. To attract and retain this level of talent, teams are investing in best-in-class tools so they have the best possible research environment. And they are automating key parts of the process like model optimization so their teams are as productive as possible.
Rely on a Solution Built for the Enterprise
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Modular
SigOpt is easy to embed in any machine learning platform with a few lines of code. We are built to fit into your workflow, regardless of how you design it today or change it tomorrow.
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Proven
Augment your experts with model optimization so they can develop high-performing models at a much faster rate.
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Scalable
Automate optimization for any model with our API-enabled solution, whether the model has 100 hyperparameters, requires 100x parallelism to tune or can benefit from advanced optimization techniques like multimetric or multitask.
Outperform Other Optimizers
Accelerate Wall-Clock Time to Tune
SigOpt’s proprietary solution efficiently explores and exploits your search space to uncover the global optima for any model much faster than grid search, random search or open source Bayesian optimization.
Earn a Return on your Machine Learning
Augment Expert Productivity
“We can keep our experts focused on the tasks core to our business, and entrust the SigOpt platform to find the optimal hyperparameter configurations.”
Dr. John Platt
Deep Learning Engineer
Carbon Relay
Amplify Impact of Your Models
“We’ve integrated SigOpt’s optimization service and are now able to get better results faster and cheaper than any solution we’ve seen before.”
Matt Adereth
Managing Director
Two Sigma
Accelerate Model Development
“Integrating SigOpt into our modeling platform empowers our team to more efficiently experiment, optimize and, ultimately, model at scale.”
Peter Welinder
Research Scientist
OpenAI
SigOpt for Enterprise
SigOpt is carefully designed with our enterprise customers in mind. We built an API-enabled user experience that fits into your existing workflow so you can continue to optimize models using our solution regardless of how your infrastructure, stack, team, or workflow evolves over time. Our black-box Optimization Engine is enhanced with applied optimization techniques to meet your evolving model tuning needs. And our Experiment Insights dashboard empowers your researchers to introspect and reproduce experiments through the model development process.
Algorithmic Trading
Unlock new trading strategies with advanced optimization techniques for model pipelines and backtests.
Finance & Insurance
Improve fraud detection, reduce credit risk and manage loan portfolios with higher-performing models.
SigOpt for Academia
SigOpt’s mission is to empower the world’s experts. To fulfill this mission, we provide a free version of our solution to academics who have encountered the painful process of tackling hyperparameter tuning with manual, grid, random, or open source Bayesian techniques.
Interested in SigOpt by Model Type?
As a black-box optimization solution, SigOpt tunes any model’s hyperparameters without touching the underlying data or model. Our customers have used us on a wide variety of model and problem types, but the categories below represent a few of the most common modeling use cases for which we have developed unique features.
Machine Learning
SigOpt is easy to embed in any modeling pipeline to optimize any variety, volume or complexity of machine learning models. This approach ensures your machine learning pipelines will be optimized even as you evolve your infrastructure and workflow.
Deep Learning
SigOpt enables even the most complex models with up to 100 hyperparameters and requiring up to 100x parallelism. And our solution includes techniques like Conditional Parameters and Multi-task Optimization so that these more expensive functions – and their architecture – can be optimized.