# What are the leading machine learning services for enterprise?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">We're evaluating machine learning platforms that can support enterprise-scale data operations and AI development. The right solution should offer scalability, strong security, and tools for collaboration across data science, engineering, and business teams.</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Here are a few <a class="a a--md" elv="true" href="https://www.g2.com/categories/data-science-and-machine-learning-platforms">machine learning services</a> I’m currently reviewing. I’d love to hear from anyone who has used them in an enterprise environment.</p><ul>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/google-vertex-ai/reviews">Vertex AI</a>: Built on Google Cloud and designed to manage the full ML lifecycle. Good option for teams already invested in Google’s ecosystem.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/databricks-data-intelligence-platform/reviews">Databricks Data Intelligence Platform</a>: Unified platform for data engineering, analytics, and machine learning. Works well for organizations managing large datasets and collaborative workflows.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/deepnote/reviews">Deepnote</a>: Collaborative data notebooks with real-time editing. Ideal for teams that prioritize quick experimentation and seamless sharing.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/dataiku/reviews">Dataiku</a>: Enterprise-ready platform that supports visual workflows and code-first development. Great for connecting data scientists and business analysts.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/saturn-cloud-saturn-cloud/reviews">Saturn Cloud</a>: Scalable cloud environment for heavy-duty ML workloads in Python. Designed to handle parallel compute with minimal infrastructure hassle.</li>
</ul><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">If your team has used any of these platforms at scale, I’d love to hear how they performed under enterprise conditions, what challenges you ran into, and what stood out in terms of speed, collaboration, or model deployment.</p>

##### Post Metadata
- Posted at: about 1 year ago
- Author title: BBCOR Tester
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;Definitely check out Vertex, especially if you&#39;re using Google products already &lt;/p&gt;

##### Comment Metadata
- Posted at: about 1 year ago
- Author title: G2 user since 2020
- Net upvotes: 1




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