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Self-hosted AI vs. cloud AI
Where the data goes, who owns compliance, and what the trade-offs actually are. Concrete, not philosophical.
- Compared with
- Cloud AI (Bedrock, Azure AI, Vertex AI)
- Updated
- 2026-07-23
Cloud AI platforms (AWS Bedrock, Azure AI, Vertex AI) route customer data through their own infrastructure. Self-hosted AI runs the runtime and the model inside the customer's environment. The AI applications, called Intelligence Packs, execute where the data already lives. A self-hosted deployment typically reaches production in weeks: slower than a cloud AI demo (days) but far faster than the 12-18 months a fully custom on-prem build normally takes, and without the vendor lock-in cloud AI creates.
SIDE BY SIDE
Is self-hosted AI slower to deploy than cloud AI like Bedrock or Azure AI?
| Dimension | Huitzo | Cloud AI (Bedrock, Azure AI, Vertex AI) |
|---|---|---|
| Where data is processed | Customer environment | Vendor cloud |
| Model portability | Model-agnostic | Vendor catalog only |
| Air-gapped operation | Supported | Not supported |
| Compliance ownership | Customer environment | Vendor SOC 2 + customer BAA |
| Time to first deployment | Weeks | Days, but couples to vendor |
QUESTIONS
When should I choose self-hosted AI over cloud AI?
When is cloud AI the right answer?
When the workload is not subject to data-residency or sovereignty constraints and time-to-first-deployment matters more than portability. Cloud AI is faster to prototype against; the lock-in shows up later.
Does self-hosted AI mean self-managed infrastructure?
Yes, the customer operates the infrastructure. The Huitzo runtime is one Linux service inside an environment the customer already operates.
AI operating system for regulated companies
Simple by design. Built to scale. Runs where your data lives.
- Product access
- Huitzo Hub is available by invitation for teams evaluating the product.