# Self-Hosted AI vs AWS Bedrock & Amazon Q

> Source: https://ibl.ai/resources/comparisons/self-hosted-ai-vs-aws-bedrock


*An owned, model-agnostic, deploy-anywhere AI platform — vs. AWS-native Bedrock + Amazon Q for building agents and enterprise assistants*

AWS Bedrock gives enterprises an AWS-native way to access multiple foundation models (Anthropic, Meta, Cohere, Amazon, and others) through one API; Amazon Q layers an enterprise assistant on top. The pair runs on AWS, integrates with the broader AWS stack, and the model selection is curated by Amazon.

Self-hosted AI is a different shape: a model-agnostic platform you own, that runs on any cloud, on-premise, or fully air-gapped. You bring any LLM — including any of Bedrock's hosted models — and operate the platform under perpetual license.

Both are legitimate enterprise options. The decision is whether you want a deeply AWS-native multi-model service, or an owned platform that can run anywhere and route to any model.

## Feature Comparison

### Platform Capabilities

| Criteria | Self-Hosted AI | AWS Bedrock + Amazon Q |
|----------|--------------------|--------------------|
| Foundation Model Catalog | Run any open or commercial model — including Anthropic Claude and others Bedrock offers — through your own routing layer. | Strong multi-model API: Anthropic, Meta, Cohere, Amazon, and others, all managed inside Bedrock. |
| Agent & Workflow Builder | Full agentic OS — agents, workflows, learning, and content — owned end to end. | Bedrock Agents and Q's enterprise assistant capabilities, bounded to AWS's runtime. |
| Enterprise Search & RAG | Permissions-aware retrieval over your knowledge, with embeddings of your choice. | Strong RAG via Bedrock Knowledge Bases and the AWS data plane. |
| Any-LLM Routing | Route any LLM by cost, latency, and capability — switch per workload, on-prem and air-gapped included. | Routing across Bedrock's hosted models; non-Bedrock models require integration work. |

### Ownership & Cloud Posture

| Criteria | Self-Hosted AI | AWS Bedrock + Amazon Q |
|----------|--------------------|--------------------|
| Multi-Cloud / On-Prem / Air-Gapped | Run on AWS, Azure, GCP, on-premise, or fully air-gapped — same platform across environments. | AWS-native; on-prem options (Outposts) are limited; not built for air-gap. |
| Data Sovereignty & Residency | Prompts, embeddings, and audit logs stay entirely in your environment. | Strong AWS region controls; data is processed in the AWS cloud under shared-responsibility. |
| Source-Code & Platform Ownership | Own the full platform code under perpetual license — fork, extend, exit. | Managed cloud service; you consume Bedrock and Q rather than owning the platform. |
| Cloud Vendor Lock-In | Cloud-agnostic — migration between clouds doesn't change the platform. | Tied to AWS account, Bedrock/Q services, and AWS pricing. |

### Cost & Compliance

| Criteria | Self-Hosted AI | AWS Bedrock + Amazon Q |
|----------|--------------------|--------------------|
| Cost Model at Scale | Flat platform fee + usage on compute you own; cost grows with consumption, not seats or services. | AWS consumption + Bedrock/Q service fees; predictable but tied to AWS pricing. |
| Compliance Fit (HIPAA / FedRAMP / FERPA / NIST) | Compliance posture sits inside your perimeter; air-gap satisfies the strictest mandates. | Broad AWS compliance coverage, including GovCloud for federal workloads. |
| Time-to-Value | Requires infrastructure and setup, or a partner to deploy and operate it. | Turn on Bedrock and Q in your AWS account and ship quickly for AWS-standardized teams. |
| Support & Service Catalog | Forward-deployed engineering + enterprise support across the platform. | AWS enterprise support and the broader AWS service ecosystem. |

## Detailed Analysis

### AWS-Native Multi-Model vs an Owned Platform

**Self-Hosted AI:** Self-hosted AI is the right shape when ownership, multi-cloud, and air-gap matter — when you want one platform across AWS, Azure, GCP, on-prem, and air-gapped.

**AWS Bedrock + Amazon Q:** Bedrock + Q are the right shape when AWS is the strategic cloud and a curated multi-model API across Bedrock's roster fits your needs.

**Verdict:** Choose Bedrock + Q for AWS depth and a multi-vendor model API; choose self-hosted AI when you want one owned platform across clouds and deployment models.

### Model Freedom vs Curated Catalog

**Self-Hosted AI:** A model-agnostic platform runs any LLM — including all the models Bedrock offers — and routes per workload as the frontier moves, including local and open models.

**AWS Bedrock + Amazon Q:** Bedrock offers strong third-party model breadth, but the catalog is curated and routing lives inside AWS.

**Verdict:** If running open / local models alongside frontier ones matters, self-hosted AI fits; if Bedrock's catalog covers your needs, Bedrock + Q is sufficient.

### Lock-In: Cloud + Catalog vs Cloud-Agnostic + Owned

**Self-Hosted AI:** Owning the platform code on infrastructure you choose means migrations between clouds don't replatform your AI — and air-gap is always an option.

**AWS Bedrock + Amazon Q:** Bedrock + Q assume AWS as the durable strategic cloud; leaving AWS means rebuilding the AI layer.

**Verdict:** For organizations that want optionality on cloud and models simultaneously, the owned platform wins on lock-in posture.

## FAQ

**Q: Is ibl.ai an alternative to AWS Bedrock?**

Yes. Both let enterprises build AI on multiple models; ibl.ai is model-agnostic and owned, running on any cloud or on-prem, while Bedrock is AWS-native and consumed as a managed service.

**Q: Can I still use Bedrock's models on a self-hosted platform?**

Yes. ibl.ai is model-agnostic, so the models Bedrock hosts (Anthropic, Meta, Cohere, Amazon, others) can be routed alongside open and local models — without tying your platform to AWS.

**Q: Can ibl.ai run on AWS?**

Yes. It deploys on AWS, Azure, GCP, or on-premise — the same platform across environments, including in your AWS VPC as a managed VPC deployment.

**Q: Can it run air-gapped, unlike Bedrock?**

Yes. ibl.ai can run fully on-premise or air-gapped with local models and zero external calls; Bedrock + Q are managed cloud services and are not built for air-gap.

**Q: Is ibl.ai cheaper than Bedrock + Q at scale?**

Often, because cost grows with consumption on compute you own rather than across an AWS service catalog, and you're not paying AWS's premium for every adjacent service.

**Q: How does ibl.ai fit in?**

ibl.ai is a model-agnostic, self-hosted AI Operating System you own and run on any cloud, on-premise, or air-gapped — for enterprise agents and apps, with SOC 2, HIPAA, and FERPA compliance by design.