# What is the most recommended generative AI infrastructure for software companies?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">I’m researching the top generative AI infrastructure platforms that software companies are actually using and recommending.</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">For dev-heavy teams building AI features into products, infrastructure matters. You need something that balances model access, training tools, performance, and long-term flexibility. Based on <a class="a a--md" elv="true" href="https://www.g2.com/categories/generative-ai-infrastructure">generative AI infrastructure tools</a> on G2, these are the providers I’m seeing most often. Curious what your experience has been with any of them.</p><ol>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/google-vertex-ai/reviews"><strong>Vertex AI</strong></a><strong>:</strong> Google Cloud’s end-to-end machine learning platform. Great for teams that want tight integration across model training, tuning, and deployment workflows.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/aws-bedrock/reviews"><strong>AWS Bedrock</strong></a><strong>:</strong> API-based access to models from providers like Anthropic and Meta. Solid option for software companies already working within AWS infrastructure.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/zoom-workplace/reviews"><strong>Zoom Workplace</strong></a><strong>:</strong> Primarily a collaboration tool, but it now includes generative AI features. May be helpful for companies building productivity features into their apps.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/google-cloud-ai-infrastructure/reviews"><strong>Google Cloud AI Infrastructure</strong></a><strong>:</strong> Under-the-hood compute and storage infrastructure with TPU support. Designed for high-scale training and inference.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/botpress/reviews"><strong>Botpress</strong></a><strong>:</strong> Open-source platform for conversational AI. Developer-friendly and popular with teams building custom assistants and chatbot interfaces.</li>
</ol><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Which one have you found most reliable or flexible in a software development environment? I’d love to hear what’s worked for your team, especially if you’ve tested more than one of these options.</p>

##### Post Metadata
- Posted at: about 1 year ago
- Author title: BBCOR Tester
- Net upvotes: 3


## Comments
### Comment 1

From a technical POV reliability depends on team goals. Vertex AI is strong for integrated ML workflows while AWS Bedrock fits best for API-based access in AWS native stacks. Google Cloud AI Infra shines for high scale training with TPUs. Botpress is solid for conversational AI flexibility. At CONTUS Tech, we have seen AI development companies prefer Vertex for end-to-end control but Bedrock offers faster integration for product teams prioritizing speed.

##### Comment Metadata
- Posted at: 10 months ago
- Author title: Digital marketing executive



### Comment 2

&lt;p&gt;I’ve heard Vertex AI is a solid option for generative AI infrastructure. Has anyone here used it for software development workflows? Curious how it handles customization and scaling.&lt;/p&gt;

##### Comment Metadata
- Posted at: about 1 year ago
- Author title: BBCOR Tester





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