Intel SigOpt banner

Intel SigOpt

Build the best models
Intel SigOpt Overview

SigOpt is a model development platform that makes it easy to track runs, visualize training, and scale hyperparameter optimization for any type of model built with any library on any infrastructure

  • System-wide Features:
  • Teamwork and Collaboration
  • Enterprise Security
  • Governance
  • Enterprise Support
  • MLOps Features:
  • Data Acquisition
  • Data Versioning
  • Data Visualization
  • Data Preparation
  • Data Pipelines
  • Data Labeling
  • AutoML
  • Featurization
  • Feature Store
  • ML Pipelines or Workflows
  • Model Registry
  • Model Marketplace
  • Model Training
  • Distributed Model Training
  • Model Debugging
  • Experiment Management
  • Deep Learning Support
  • Reinforcement Learning Support
  • Bias Detection and Mitigation
  • Model Explainability
  • Hyperparameter Optimization
  • Model Packaging
  • Model Deployment and Serving
  • Edge ML Support
  • Model Monitoring
  • Cost Management
  • ML Infrastructure Orchestration
  • Accelerator Support
  • Kubernetes Support

Have you used Intel SigOpt?

If so, please share your experiences with the TWIML community.
Additional Product Information
Product Links
Deploys On
  • Amazon Web Services
  • Google Cloud Platform
  • Microsoft Azure
  • Other Public Cloud
  • Kubernetes
  • Private Cloud or Datacenter
  • SaaS
Intel SigOpt Features and Benefits

*Performance: Accelerate hyperparameter optimization jobs by up to 10x faster than other intelligent optimization methods and up to 100x times faster than naive grid and random search

*Productivity: Reduce time to a viable model by 30% by automating tasks like hyperparameter tuning and logging, and providing more seamless opportunity for collaboration in our dashboard

*Efficiency: Scale across your full compute bandwidth seamlessly regardless of your infrastructure or the modeling library you are applying to save wall-clock time and reduce the number of training runs required to get to a viable performance threshold to save total compute required for your modeling project

*Portability: Use SigOpt across all environments, libraries, tasks without adjusting your workflow to avoid vendor lock-in and future-proof your modeling process.


*Experiment design: Define strategies for metrics, parameters, and compute that set training and optimization up for success.

*Model Exploration: Automatically track modeling artifacts during training runs, seamlessly apply active search to explore your parameter space, and visualize checkpoints, metrics, and parallel coordinates to deeply understand your model's behavior

*Model Optimization: Apply any optimizer of your choice within SigOpt or use SigOpt's proprietary optimizer for hyperparameter tuning, run in parallel to utilize your full compute, and utilize advanced research features to uncover novel insights on your modeling problem

*Dashboard: Log your full history of all runs and experiments, capture code snapshots, collaborate on modeling projects, manage user permissions, compare models, and visualize training curves.

*Open and Agnostic: Run SigOpt in any coding environment across any compute infrastructure on any modeling problem with any modeling library without adjusting your workflow.

SigOpt Vendor Information
Vendor Overview
SigOpt is the only experimentation platform that empowers AI developers to design experiments, explore their modeling problem space, and optimize model selection. By combining seamless experimentation with powerful optimization, SigOpt helps teams like Two Sigma realize 8x faster hyperparameter optimization and OpenAI scale their experiments with sample efficiency to maximize compute utilization.
Vendor Details
Year Founded
HQ Location
San Francisco, California, United States

Contact Request

No data was found

Sorry. This form is no longer accepting new submissions.

Submit Review for Intel SigOpt

Sorry. This form is no longer accepting new submissions.