What is the difference between AWS Bedrock and PromptUnit?

Bedrock is AWS's managed platform for using and deploying foundation models inside your AWS account, with AWS security and compliance. PromptUnit sits in front of the providers you already use and checks each request, using a cheaper model when one is just as good for it.

Does AWS Bedrock route requests to cheaper models?

Bedrock's Intelligent Prompt Routing chooses between models of one family, for example Claude Sonnet and Claude Haiku. AWS puts the saving at up to 30%. It does not route from one model family to another, such as from Claude to an OpenAI model.

Does PromptUnit work with AWS Bedrock?

Not directly. PromptUnit works with your own OpenAI, Anthropic, Google Gemini, Groq and DeepSeek keys, and with your own OpenRouter key; it does not call models through Bedrock.

Does PromptUnit have SOC 2 or FedRAMP?

No. PromptUnit has no SOC 2 report or FedRAMP authorization yet. If your organization requires them today, Bedrock inside your AWS account is the option that meets that requirement.

PromptUnit vs AWS Bedrock: Platform vs Cost Optimization

AWS Bedrock and PromptUnit are not the same category of tool. Bedrock is a managed AWS platform for accessing and deploying foundation models. PromptUnit is a cost optimization layer that sits between your existing code and your AI providers.

The comparison is worth making because teams evaluating how to manage LLM costs often consider both. They serve overlapping use cases but with very different trade-offs.

What AWS Bedrock Actually Is

Amazon Bedrock is a fully managed service that provides API access to foundation models from multiple providers through the AWS ecosystem. Supported providers include Anthropic (Claude), Meta (Llama), Mistral, Google (Gemma), DeepSeek, and OpenAI models: AWS's OpenAI on Bedrock page lists GPT-6 Astra, GPT-6.1 Sol, GPT-6 Sol, GPT-6 Luna and the GPT-5.6 models, after GPT-5.5 and GPT-5.4 became generally available in June 2026.

Bedrock integrates tightly with AWS infrastructure: IAM for authentication, CloudWatch for monitoring, CloudTrail for audit logs, and PrivateLink for private networking. For teams already running on AWS, this is a real operational advantage.

What Bedrock does well:

Unified API access to multiple model providers within AWS
Enterprise security and compliance (FedRAMP High, HIPAA eligible, SOC 2)
IAM-based access control and CloudTrail audit logging
Prompt caching for supported models (up to 90% cost reduction on cached input)
Intelligent Prompt Routing within the same model family (up to 30% cost reduction)
Model fine-tuning and customization via Knowledge Bases
Guardrails for content filtering and hallucination reduction
Native integration with AWS services (Lambda, SageMaker, S3)

What Bedrock does not do:

Route requests across different provider families. Bedrock's Intelligent Prompt Routing works within a single model family, for example between Claude Sonnet and Claude Haiku, not from Claude to an OpenAI model such as GPT-6 Luna.
Work with your existing OpenAI SDK without code changes. Bedrock uses its own API format and authentication (IAM Signature V4), requiring migration of existing OpenAI-based code.
Show the savings on each request, starting with the first one.
Price itself based on what it saves you.

Bedrock pricing note: On-demand token pricing is the same as the providers' direct APIs. Provisioned Throughput, which reserves capacity and guarantees throughput, is billed by the hour per model unit, at a price that depends on the model, instead of per token. For variable workloads, on-demand is usually the right choice. For high-volume steady workloads, Provisioned Throughput can reduce per-token costs.

What PromptUnit Actually Is

PromptUnit is an LLM cost optimization engine. Setup is one change: you paste your personal PromptUnit address where your app's AI address (base URL) is set, and your existing OpenAI SDK code stays as it is. Your AI key stays in your app; PromptUnit never asks for it and does not store or log it. No AWS account required, no IAM setup, no SDK migration.

The routing engine classifies each request by task type and complexity, then uses the cheapest model that clears your quality setting. With no key saved in PromptUnit, requests move only between the same provider's models. If you choose to save another provider's key on the dashboard's Connection page (it is saved encrypted), this becomes cross-provider routing: a request sent to an OpenAI model can be answered by Claude Haiku or Gemini Flash when they meet the quality bar at lower cost.

Pricing is 20% of verified savings only. If routing saves nothing in a billing cycle, you pay nothing.

What PromptUnit does well:

Cross-provider cost-optimizing routing (not limited to one model family)
One address to paste (your personal PromptUnit address as the base URL), existing OpenAI SDK code unchanged
Savings from the first request, with every request shown on the dashboard
Savings attribution by feature, model, and task type
Retries on the model you asked for when a cheaper model it chose fails
Pay-only-for-savings pricing model

What PromptUnit does not do:

Switch to another provider when your provider is down
Replace AWS infrastructure or integrate with IAM, CloudWatch, or CloudTrail
Provide model fine-tuning or customization
Hold enterprise compliance certifications (no SOC 2 report yet)
Offer Provisioned Throughput or reserved capacity pricing

Comparison Table

Property	AWS Bedrock	PromptUnit
Primary purpose	Managed AI platform on AWS	LLM cost optimization
Integration	AWS SDK, IAM auth, code migration required	One address to paste as the base URL; existing OpenAI SDK and your own key stay
Routing type	Within same model family only	Cross-provider (OpenAI, Anthropic, Google, Groq, DeepSeek)
Routing savings	Up to 30% (AWS figure for Intelligent Prompt Routing)	40-70% (our estimate for cross-provider routing on mostly simple requests, not a guarantee)
Per-request savings view	No	Yes, from the first request
AWS-native	Yes	No
Requires AWS account	Yes	No
Pricing	Pay per token (same as direct API)	20% of verified savings
Enterprise compliance	FedRAMP High, HIPAA, SOC 2	None yet
Model fine-tuning	Yes	No
Failover	Within Bedrock-supported models	Retries on your requested model if a cheaper one fails; no cross-provider failover

Which to Choose

Choose AWS Bedrock if:

Your infrastructure already runs on AWS and you want tight IAM integration
Enterprise compliance certifications are required now (FedRAMP, HIPAA)
You need model fine-tuning or customization capabilities
You want a single AWS-billed service for model access
Provisioned Throughput for guaranteed capacity is a requirement
You are building new infrastructure from scratch and are not already using the OpenAI SDK

Choose PromptUnit if:

You have existing code using the OpenAI SDK and want to reduce costs without a migration
Your primary goal is cutting LLM inference spend automatically across providers
You do not want to manage AWS IAM permissions and Bedrock-specific configuration
You want cross-provider routing, not just routing within one model family
Pay-for-results pricing fits better than per-token billing at standard rates
You want to see what each request cost and saved, starting with the first one

The Core Difference

AWS Bedrock is a platform. It gives you infrastructure for deploying, managing, and securing AI models within AWS. It is the right choice when you need enterprise-grade AWS-native AI infrastructure.

PromptUnit is a cost optimization layer. It sits on top of your existing provider relationships and reduces the bill automatically. It is the right choice when you have working AI infrastructure and want to reduce what you pay for it, without rebuilding anything.

They can coexist: teams running on Bedrock for compliance or AWS integration can layer PromptUnit on top to optimize routing across non-Bedrock providers or for workloads that do not require Bedrock's enterprise features.

If your problem is: "I need an enterprise AI platform deeply integrated with AWS", use Bedrock.

If your problem is: "My LLM bill is too high and I want to reduce it without rewriting my stack", use PromptUnit.

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One address to paste. Savings from the first request. Pay only from savings.

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