Govern Every Amazon Bedrock Model Call Across AWS

Q: "How does Raidu integrate with Amazon Bedrock?"

"Raidu integrates at the API layer, intercepting Bedrock API calls before they reach the foundation models. This can be configured through API gateway integration, SDK wrapper, or network level interception depending on your architecture. The integration works with all Bedrock supported models and requires no changes to your application code."

Q: "Can Raidu enforce different policies for different Bedrock models?"

"Yes. Raidu supports model specific policy configuration. You might allow customer support teams to use Titan for general queries with standard PII masking, while requiring stricter controls and additional approval for Claude or Llama when processing sensitive healthcare data. Each model and use case combination gets the appropriate governance profile."

Q: "Does Raidu work with Bedrock's custom model and fine tuning features?"

"Yes. Raidu governs the inference layer, meaning it works with any model accessible through Bedrock's API, including custom models and fine tuned variants. The training data governance for fine tuning is handled separately, but every inference call to your custom models passes through Raidu's policy enforcement."

Q: "How does Raidu handle Bedrock usage across multiple AWS accounts?"

"Raidu provides centralized governance regardless of how many AWS accounts or regions your organization uses. Each Bedrock deployment connects to Raidu's governance layer, and all policies, audit trails, and compliance records are managed from a single control plane. Your security team gets unified visibility without chasing data across accounts."

Bedrock gives your teams access to dozens of foundation models through a single API. Raidu ensures that every call to every model is governed by your organization's policies, with cryptographic proof that compliance was enforced.

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Amazon Bedrock

AWS managed foundation model service

Amazon Bedrock provides serverless access to foundation models from Anthropic, Meta, Cohere, and others through a unified AWS API. Enterprises use Bedrock to build AI applications within their AWS infrastructure.

The Governance Risks

AI adoption without governance creates risk.

Multiple Foundation Models, Inconsistent Governance

Bedrock offers models from Anthropic, Meta, Cohere, AI21, Stability, and Amazon itself. Each model has different capabilities and risk profiles, but most organizations apply the same generic controls to all of them. Without model aware governance, sensitive data may flow to models with weaker safety properties.

Decentralized Usage Across AWS Accounts and Regions

Large enterprises run Bedrock across multiple AWS accounts, regions, and environments. Development teams spin up Bedrock access independently, creating governance fragmentation. Without centralized visibility, your security team cannot answer basic questions about which models are being used, by whom, and with what data.

Compliance Burden for Regulated Industries on AWS

Healthcare, financial services, and government organizations on AWS face strict regulatory requirements for AI usage. HIPAA, FedRAMP, SOX, and the EU AI Act all require demonstrable governance over AI systems. AWS provides infrastructure compliance, but the governance of what your applications do with Bedrock is your responsibility.

No Native Cost Governance or Model Selection Controls

Bedrock makes it easy for any developer with API access to call expensive models like Claude 3 Opus or Llama 3 70B. Without cost controls and model selection policies, a single team can generate significant unexpected charges. More critically, teams may use models that are not approved for their use case or data sensitivity level.

How Raidu Solves This

Purpose-built AI governance that works with your existing tools.

Consistent Policy Enforcement Across All Bedrock Models

Raidu applies your governance policies uniformly across every foundation model available in Bedrock. Whether a developer calls Claude, Llama, or Titan, the same PII masking, content filtering, and data protection rules are enforced. Your policies follow the interaction, not the model.

Centralized Visibility Across AWS Accounts and Regions

Raidu aggregates Bedrock usage data from every AWS account and region into a single governance dashboard. Your security team sees exactly which models are being called, what data is being sent, and which policies are being applied. No more blind spots across your AWS footprint.

Cryptographic Compliance Proof for Every API Call

Every Bedrock API call governed by Raidu generates a tamper proof audit record. RSA-4096 digital signatures and SHA-256 hash chains create mathematically verifiable evidence that your policies were enforced. When auditors ask about your AI governance, you provide proof, not promises.

Cost Controls and Model Access Governance

Raidu lets you define which teams can access which Bedrock models based on role, use case, and data sensitivity. You can set spending limits per team or per model, route requests to cost effective models when appropriate, and ensure that expensive or unapproved models are only accessible to authorized users.

SOC 2 Type II (pursuing)

Typically <50ms Added Latency

On-Premise Available

Input + Output Protection

Frequently Asked Questions

How does Raidu integrate with Amazon Bedrock?

Raidu integrates at the API layer, intercepting Bedrock API calls before they reach the foundation models. This can be configured through API gateway integration, SDK wrapper, or network level interception depending on your architecture. The integration works with all Bedrock supported models and requires no changes to your application code.

Can Raidu enforce different policies for different Bedrock models?

Yes. Raidu supports model specific policy configuration. You might allow customer support teams to use Titan for general queries with standard PII masking, while requiring stricter controls and additional approval for Claude or Llama when processing sensitive healthcare data. Each model and use case combination gets the appropriate governance profile.

Does Raidu work with Bedrock's custom model and fine tuning features?

Yes. Raidu governs the inference layer, meaning it works with any model accessible through Bedrock's API, including custom models and fine tuned variants. The training data governance for fine tuning is handled separately, but every inference call to your custom models passes through Raidu's policy enforcement.

How does Raidu handle Bedrock usage across multiple AWS accounts?

Raidu provides centralized governance regardless of how many AWS accounts or regions your organization uses. Each Bedrock deployment connects to Raidu's governance layer, and all policies, audit trails, and compliance records are managed from a single control plane. Your security team gets unified visibility without chasing data across accounts.

Govern Amazon Bedrock Across Your Entire AWS Environment

Enforce consistent policies across every foundation model in Bedrock and prove compliance with cryptographic evidence.

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