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Iterative

Developer tools for Machine Learning | Iterative

Iterative Careers
Iterative is a leading company specializing in providing developer tools for Machine Learning (ML). With a strong reputation and trust from hundreds of ML teams, ranging from startups to Fortune 500 companies, Iterative offers a comprehensive suite of AI tools designed to supercharge collaboration and productivity across ML teams. At Iterative, we understand the challenges faced by data scientists and machine learning engineers. That's why our mission is to empower them by providing the necessary tools and infrastructure to streamline their workflow and improve productivity. Our suite of tools enables users to version control their data and ML experiments, ensuring reproducibility and easy collaboration. One of the key features of Iterative's platform is the ability to manage data effectively. Users can version data stored across any cloud and easily manage labels and annotations. By automating these processes, Iterative enables ML teams to streamline their data management tasks. In addition to data management, Iterative also offers tools for developing ML models. Our platform supports model development across the entire ML lifecycle, providing experiment versioning and tracking capabilities. This allows users to efficiently iterate on their models and keep track of their progress. Furthermore, Iterative's platform facilitates the training and deployment of ML models. Users can automate training on any cloud and access live reports to monitor the progress of their models. This automation helps save time and resources for ML teams. Collaboration is another essential aspect of Iterative's platform. Users can build and share dashboards of experiments, allowing for easy collaboration and knowledge sharing within the ML team. Additionally, Iterative provides tools to manage models from development to production and retirement, ensuring a smooth transition throughout the entire model lifecycle. In addition to our core tools, Iterative offers several specialized tools to enhance the ML workflow. Our Data Version Control (DVC) tool enables faster model building through data and experiment versioning and reproducible pipelines. The Model Lifecycle Extension Manager (MLEM) simplifies model deployments by extracting model metadata and building a model registry. The Continuous Machine Learning (CML) tool automates ML experiments using CI/CD automation across any cloud. The Studio tool allows for collaboration across the ML team with experiment tracking and visualization. The Terraform Plugin for Iterative (TPI) is specifically designed for machine learning projects using Terraform. Additionally, Iterative provides a VS Code Extension for seamless integration with the popular code editor. By utilizing Iterative's tools, ML teams can accelerate their time-to-market by managing and versioning data, experiments, and models, ensuring instant reproducibility. The platform also improves collaboration by enabling knowledge sharing through custom dashboards and encouraging discussions around models. Additionally, Iterative's tools centralize visibility and governance, allowing users to track the progress of ML projects and ensure data and model lineage details for governance and regulatory compliance. With over 250 open-source contributors, 7000+ community members, and over 500 companies relying on our tools, Iterative has established itself as a trusted and popular choice in the ML community. Our platform has received over 14,000 Github Stars, showcasing its popularity and credibility in the industry. Join our community today and take advantage of our powerful tools to accelerate your ML workflow and achieve better results. Visit our website to explore the benefits of version controlling data and ML experiments and start your free trial. At Iterative, we are committed to empowering ML teams and driving innovation in the field of Machine Learning.
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Iterative

Industry
Software Development
Year founded
2018
Company size
11-50
HQ Location
United States, California, San Francisco
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