Managed model service on AWS
INFRO vs Amazon Bedrock
Amazon Bedrock runs models from many vendors inside AWS, under AWS identity, networking and billing. Around the models it carries a governance surface that many teams use as their gateway: cross-Region inference profiles, cost allocation tags through application inference profiles and Projects, Bedrock Guardrails, IAM policies per model, and model invocation logging. For a company that runs on AWS and wants its model spend on its AWS bill, it is the natural home, and for many of them the evaluation should end there.
- You run on AWS and want every model call inside your AWS accounts, under IAM, your VPC and your existing AWS agreements. Bedrock is all of that by construction; INFRO is one more vendor in the request path.
- Your company has committed AWS spend. Model usage on Bedrock is AWS usage on your AWS bill; usage on a direct provider contract routed through INFRO is not.
- The models you need are on Bedrock. If one cloud catalog covers your workloads, there is no second provider for a cross-provider control plane to span.
- Safety policy is the requirement. Bedrock Guardrails carries content filters, denied topics, sensitive-information filters, contextual grounding checks and Automated Reasoning checks, and its ApplyGuardrail API checks text without invoking a model. INFRO's guardrails are pattern checks for PII, secrets and your own terms on chat completions, with optional classifier checks run on a decision model you connect, from the Business plan.
- You want cost by team in AWS Cost Explorer and the Cost and Usage Report, beside the rest of your AWS spend, in billed dollars rather than an estimate.
This section is not a courtesy. If one of these describes you, pick Amazon Bedrock — a customer who adopts the wrong layer on our advice is worse for us than one we never had.
Where the two actually diverge.
- One cloud's catalog, or every account you hold
- Bedrock governs the models Bedrock serves. Your direct OpenAI or Anthropic contract, a Gemini key on Google Cloud and an Azure OpenAI deployment sit outside it, each with its own limits, logs and cost view. INFRO's unit is the set of provider accounts your company already pays for, so one policy, one budget and one request record can span all of them — Bedrock included.
- Billed dollars a day later, or an estimate on every request
- AWS's cost attribution is the real bill: application inference profiles and Projects carry tags into Cost Explorer and the Cost and Usage Report. AWS's own pages describe the trade that comes with it — the finest grain is per usage type per day, not per request; activated tags can take up to 24 hours to appear and are not retroactive; and an application inference profile is tied to one model, so each combination of model, team and tag set needs its own. INFRO prices every request as it happens, from the vendor's published rate or from your negotiated rates on the Team plan, and attributes it to a project, key, model, route or end user. That number is an estimate rather than an invoice, which is why the Business plan checks the month against OpenAI's and Anthropic's own cost APIs and states the variance.
- Alerts and deny policies, or a request refused
- On AWS, spend control is AWS Budgets: alerts at thresholds, and budget actions that apply an IAM or service control policy once a threshold is crossed. That is account-level control after spend has been recorded. INFRO checks a blocking budget for an organization, project, member or key before the provider is called and refuses with 402 when there is no room; a model with no known price is refused under a blocking budget unless the owner allows unpriced traffic. It counts INFRO's estimate of provider cost, not the provider's invoice.
- Not either-or
- Bedrock can be one of the providers INFRO routes to. The connection uses a Bedrock API key against the runtime's OpenAI-compatible Chat Completions endpoint, and today it serves the OpenAI, xAI, Moonshot and MiniMax models Bedrock offers there. Claude, Llama, Nova and Cohere on Bedrock need the Converse API, which INFRO does not speak yet, so reach them through those vendors' own accounts or another cloud for now. The spend still lands on your AWS bill; INFRO adds the budgets, attribution and failover across the rest of your estate.
Side by side.
Our column carries dashes too. A comparison where one side is all checks is one nobody believes, and rightly.
| Capability | Amazon Bedrock | INFRO |
|---|---|---|
| Models from many vendors | yesBedrock's catalog, run on AWS | yeswhatever your connected providers serve |
| Your direct provider contracts | noBedrock-hosted models only | yesOpenAI, Anthropic, Google, Azure, Bedrock and more |
| Model spend on your AWS bill | yes | partialfor traffic sent to your Bedrock connection |
| Cost by team or application | partialtags; daily, billed dollars, not retroactive | yesper request: project, key, end user |
| Cost from the provider's own bill | yesCost Explorer and CUR | partialestimates; reconciled for OpenAI and Anthropic on Business |
| Budgets that refuse a request | partialAWS Budgets alerts and deny-policy actions | yesorganization, project, member, key; 402 |
| Failover | partialcross-Region inference within Bedrock | yesacross your own providers, Bedrock included |
| Guardrails | yesBedrock Guardrails and ApplyGuardrail | partialpatterns plus optional classifier checks; chat completions; Business plan |
| Access control per model | yesIAM | yesroles and allowlists at organization, project and key |
| Runs inside your cloud account | yes | partialhosted; self-hosted by enterprise agreement |
| Available today | yes | noprivate early access |
Our reading of each product's public documentation as of October 2026. We do not quote competitors' prices — theirs change and a wrong number about someone else's business is worse than none. Think a row is wrong? Tell us and we will fix it.
Work out what the difference is worth
Estimate what your current model mix costs at your providers' list rates and the plan it needs, or have us read your real usage and tell you where we would and would not help.