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Iguazio Review: A Production-First MLOps Platform for Scalable AI Deployment
What do you like best about the product?
What I like best about Iguazio is its strong focus on production-ready AI. It simplifies the ML lifecycle by integrating real-time data processing, feature engineering, and model deployment in one platform. The built-in feature store, serverless functions, and automated pipeline orchestration make deploying and managing models seamless. It’s especially useful for teams that need to move quickly from development to production without relying on multiple tools or manual steps. Iguazio is truly built for scalable, enterprise-grade AI.
What do you dislike about the product?
Iguazio is complex for beginners and lacks transparent pricing.
What problems is the product solving and how is that benefiting you?
Iguazio solves the problem of slow and fragmented ML deployment by unifying data processing, model training, and real-time serving in one platform. This helps reduce time-to-production, ensures better model monitoring, and improves collaboration between data scientists and DevOps — ultimately making AI projects faster, more reliable, and scalable for enterprise use.
Consolidated MLOps platform ideal for multi-hybrid cloud
What do you like best about the product?
The experience and interface is the same even if it is deployed in various compute environments, so you can combine different cloud or onprem resources in the same dashboard.
The solution team was helping implementation very efficiently.
The solution team was helping implementation very efficiently.
What do you dislike about the product?
There is nothing currently that disturbes me. Additional integrations are always welcome!
What problems is the product solving and how is that benefiting you?
Automation of otherwise manual AI/ML processes, less friction between different roles and handovers
Powerful MLOpls platform and amazing support
What do you like best about the product?
Iguazio brings super power in the hands of data scientists - with the push of a button, you can leverage your cloud compute for GPU accelerated model training and scale to zero for cost savings once completed. Using Kubeflow based pipelines, Iguazio enables machine learning training and deployment automation, leading to tremendous productivity improvement, and allowing an ML team to scale well beyond its normal capacity. The MLRun library further enhances the team's capabilities by implementing numerous common use cases, such as artifact logging, and experiment tracking. The Iguazio technical support team is second to none - using their deep expertise in Kubernetes, DevOps, machine learning and sofware development, they provide responsive support on a comprehensive list of topics.
What do you dislike about the product?
Troubleshooting can be simplified by making it easier to capture systems logs and share with the support team.
What problems is the product solving and how is that benefiting you?
Iguazio solves many problems for us, among them the most important are ML infrastructure management, ML automation. The benefits are productivity and cost savings.
Data science to life
What do you like best about the product?
It seamlessly takes the model to production by simplifying the data science process and saving cost using business innovation across different usecases.
What do you dislike about the product?
Nothing as such disliking factors are there as far as my experience.
What problems is the product solving and how is that benefiting you?
I developed a real time model with the help of Iguazio AI. So I am able to get the model into production in a short span of time added to that they will be providing constant support also.
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