We’re proud to share that the Iguazio MLOps Platform has been named a leader and outperformer in the GigaOm Radar for Data Science Platforms: Pure-Play Specialist and Startup Vendors report.
The GigaOm Radar reports take a forward-looking view of the market and are geared towards IT leaders tasked with evaluating solutions with an eye to the future. GigaOm analysts emphasize the value of innovation and differentiation over incumbent market position. In this Radar Report for Data Science Platforms, GigaOm gave Iguazio top scores on several evaluation metrics, including Integrated MLOps Capabilities, Data Security, Scalability, Deployment Flexibility, Usability and Integrations with Third-Party Frameworks.
Why GigaOm Named Us an Outperforming Challenger for 2022
Iguazio’s leader placement in the report highlights our differentiated capabilities and our commitment to a production-first approach to delivering AI/ML services. We’re thrilled to see the Iguazio MLOps Platform recognized for the capabilities every company should embrace when adopting MLOps and data science: End-to-end automation, ML CI/CD pipelines, scalability, feature store usage and real-time feature engineering, and more.
Of all the vendors reviewed in this report, Iguazio ranked highest for innovation, reflecting the Platform’s aggressive approach to technical innovation, over a more conservative stance. GigaOm noted that nimble startups without legacy technologies are particularly well suited to a rapidly evolving field like data science.
GigaOm analysts ranked Iguazio as an outperformer, which denotes their assessment that the Platform will progress rapidly over the next 12 to 18 months, based on strategy and pace of innovation.
What the Iguazio MLOps Platform Brings to Enterprise AI
As more organizations move to embed AI into their products and processes, technical teams are shifting their focus from one-off projects to industrialized AI factories. With the Iguazio MLOps Platform, enterprises can transform AI projects into real world business outcomes by accelerating and scaling development, deployment and management of AI services.
Iguazio takes a holistic approach to production ML, by automating and orchestrating the entire pipeline end to end. Our key components for MLOps acceleration are:
- An online and offline feature store, that handles data transformation feature engineering for real-time and batch data
- Rapid development of scalable real-time serving pipelines using serverless technology
- Built-in data and model monitoring, including drift detection and automated re-training
- Integrated CI/CD for ML across code, data and models, using mainstream ML, Git and CI/CD frameworks