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Connect AWS Bedrock to OpenEduCat

AWS Bedrock gives institutions access to multiple foundation models (Claude, Llama, Mistral, and Titan) through a single AWS API endpoint, under their existing AWS Enterprise Agreements. Through OpenEduCat's Bring Your Own Model (BYOM) feature, institutions already operating on AWS can power all 9 AI tools without establishing new vendor relationships or leaving their existing AWS security and compliance framework.

For IT teams that have invested in AWS IAM, CloudWatch, Cost Explorer, and VPC configurations, Bedrock is the most natural home for AI processing; the access controls, audit logs, regional data residency, and billing alerts are already in your existing AWS toolset.

Multi-model accessAWS IAM integrationEnterprise SLAsFERPA BAA available

How to connect AWS Bedrock to OpenEduCat

Three steps. Requires an existing AWS account with Bedrock model access enabled.

1

Enable Bedrock and request model access

In the AWS console, navigate to Amazon Bedrock in your chosen region. Request access to the foundation models you want to use: Claude, Llama, Mistral. Create an IAM user or role for OpenEduCat with Bedrock InvokeModel permissions. Generate access keys.

2

Configure in OpenEduCat BYOM settings

In your OpenEduCat admin panel, go to AI Settings > Provider Configuration. Select AWS Bedrock. Enter your AWS region, IAM access key ID, and secret access key. Specify your default model (e.g., anthropic.claude-3-5-sonnet). Save.

3

All 9 AI tools route through Bedrock

Every AI tool in OpenEduCat routes through your Bedrock endpoint in your chosen AWS region. CloudWatch logs every API call. AWS Cost Explorer tracks token usage. You can configure different Bedrock models for different AI tool categories within OpenEduCat.

Why institutions choose AWS Bedrock

Bedrock is the choice for institutions with existing AWS investments that want AI processing inside their existing infrastructure.

Institutions already operating on AWS infrastructure

Universities and school districts that host their student information systems, LMS, or administrative systems on AWS already have AWS accounts, IAM configurations, VPC setups, and compliance agreements in place. Adding AWS Bedrock for AI processing keeps all data within the same AWS infrastructure, under the same security controls, the same audit logging in CloudWatch, and billed to the same AWS account. No new vendor relationships, no new compliance reviews from scratch.

Multi-model flexibility through a single endpoint

AWS Bedrock is unique among the providers supported by OpenEduCat BYOM in that it gives you access to multiple foundation models through a single API endpoint, including Anthropic Claude models, Meta Llama models, Mistral models, and Amazon's own Titan models. This means you can configure OpenEduCat to use Claude via Bedrock for essay grading, Llama via Bedrock for the student support chatbot, and Mistral via Bedrock for quiz generation, all within a single AWS account, under a single set of IAM policies.

Enterprise SLAs and uptime commitments

AWS Bedrock is covered by AWS's enterprise service level agreements. For institutions that have purchased AWS Support plans or AWS Enterprise contracts, Bedrock is included in those support structures. This matters for procurement teams that require documented uptime commitments for any system that affects academic operations. The SLA documentation, compliance certifications (SOC 2, ISO 27001, FedRAMP), and support escalation paths are all already in place for existing AWS customers.

AWS IAM for fine-grained access control

AWS Identity and Access Management (IAM) lets institutions configure exactly which roles can invoke which Bedrock models for which use cases. An IT admin can configure a policy where the OpenEduCat service role can invoke Claude on Bedrock for the grading tool but not for student-facing tools, or limit Bedrock access to specific models, or restrict invocations to VPC endpoints only. This level of control fits naturally into institutions that have invested in an AWS security architecture.

AWS Bedrock: key specs for IT teams

FeatureDetail
Available modelsAnthropic Claude (3.5 Sonnet, 3 Opus, Haiku), Meta Llama 3.1, Mistral Large/Small, Amazon Titan, all via single Bedrock endpoint
Context windowVaries by model; Claude 3.5 Sonnet on Bedrock supports up to 200,000 tokens
Data residency optionsChoose AWS region at Bedrock setup: US, EU, Asia-Pacific, and others; data processed in selected region
Pricing modelPer input/output token billed to your AWS account; integrates with AWS Cost Explorer and billing alerts
FERPA considerationsAWS offers FERPA BAA through AWS Artifact; FedRAMP-authorized services available for qualifying institutions
GDPR considerationsAWS EU regions available; AWS GDPR DPA covers Bedrock; consult AWS Artifact for current documentation
Self-host optionNo self-hosting; in-region AWS deployment and VPC endpoint support provide geographic and network control
API compatibilityBedrock uses its own API format; OpenEduCat BYOM includes native Bedrock adapter alongside OpenAI-compatible mode

Frequently Asked Questions

When you configure AWS Bedrock as your BYOM provider, AI requests from OpenEduCat go directly to your AWS Bedrock endpoint in the region you configured. AWS processes those requests under your AWS agreement and the Bedrock data processing terms. You can use VPC endpoints to ensure Bedrock traffic never traverses the public internet; it stays within your AWS VPC. Review AWS Bedrock's data privacy documentation and the AWS BAA (available via AWS Artifact) for FERPA and HIPAA-relevant provisions. AWS has stated Bedrock does not use customer data to train foundation models.

Ready to connect AWS Bedrock to OpenEduCat?

Book a demo and we will walk through Bedrock configuration, IAM policy setup, multi-model routing, and how to align the integration with your existing AWS compliance framework.