Platform choice
AWS Bedrock vs Azure AI vs Vertex AI for existing SaaS
For an existing SaaS product the right managed AI platform is almost always the one your production data already lives in. Amazon Bedrock, Azure AI Foundry and Google Vertex AI all give you multiple frontier and open models behind one API, private networking, regional control and enterprise logging. The meaningful differences are model catalogue, identity and governance integration, and how much data you would have to move. Moving data to reach a marginally better model is usually the more expensive decision.
Side by side
| Amazon Bedrock | Azure AI Foundry | Google Vertex AI | |
|---|---|---|---|
| Best fit | Workload already on AWS | Microsoft-centric enterprise and Entra identity | Data already in BigQuery or GCP |
| Model access | Anthropic, Meta, Mistral, Amazon Nova and others | OpenAI models plus an open catalogue | Gemini plus open and partner models |
| Identity and policy | IAM, VPC endpoints, Guardrails | Entra ID, Azure Policy, content filters | IAM, VPC Service Controls, Model Armor |
| Data gravity | S3, Aurora, Redshift | Azure Storage, Fabric, Synapse | BigQuery, Cloud Storage |
| Agent tooling | Bedrock Agents and Knowledge Bases | Azure AI Agent Service | Vertex AI Agent Builder |
How to decide in one sitting
- Where does the data the model must read already live? Start there.
- Which identity provider governs your customers today? Match it rather than bridging it.
- Do enterprise customers demand region pinning, private networking or no-training guarantees? All three platforms support this; confirm it per region and per model.
- Does any single model materially outperform on your evaluation set? Test with your own cases before it decides the platform.
You do not have to pick only one
A model-agnostic layer inside your product, with typed tools and provider-independent prompts, lets you route different tasks to different providers and change your mind later without touching product code. That abstraction is cheap to build up front and expensive to retrofit.
How Datics helps
We build, modernize and migrate production SaaS and AI workloads across AWS, Azure and Google Cloud, including Bedrock, Azure AI and Vertex AI deployments inside customer-controlled environments.
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