Iguazio vs. Konan

With Iguazio we are able to scale up our organisations AI infrastructure which us vital to meet business goals and accelerate time-to-time. We are also able to manage our ML pipeline end-to-end using a full-stack,user-friendly environment, feature-rich integrated feature store and powerful data transformation and real-time feature engineering capabilities.

Incentivized

• Dynamic scaling capacity.
• Central Metadata management.
• Data ingestion and preparation.

Incentivized

• The user interface is not so much user-friendly, and easy-to-use, navigate.

Incentivized

Execution, experiment, data, model tracking, and automated deployment is done automatically through the MLRun serverless runtime engine. MLRun maintains a project hierarchy with strict membership and cross-team collaboration. End-to-end data governance is fully solidified and managed with authentication and identity management. Customers securely share data by providing access directly to it and not to copies.

Incentivized

• Is a fully integrated solution with a user-friendly portal.
• Manage our ML pipeline end-to-end using Full-stack,user friendly environment.
• Iguazio enables our teams to manage all artefacts throughout their lifecycle.
• Enhance team work and collaboration in our teams.

Incentivized