AWS Bedrock

A comprehensive platform for building and deploying generative AI applications and agents at production scale with access to hundreds of foundation models, security, and enterprise infrastructure.

End-to-end platform to build, connect, and optimize AI agents at scale with production-grade security. Supports any framework and model with no infrastructure management required.

Data customization tool that enables retrieval-augmented generation (RAG) to customize models with proprietary data while maintaining data control and privacy.

Combines OpenAI frontier models with AWS infrastructure to deliver agents with faster execution, built-in memory, and enterprise security.

Flexible batch processing capability for handling large-scale, non-real-time AI workloads cost-effectively.

Tool for automating data preparation and customization to enhance model performance with business-specific information.

Capability to fine-tune foundation models on proprietary data to optimize AI applications for specific business use cases.

Security feature that blocks harmful content (up to 88% effectiveness) and identifies correct model responses with up to 99% accuracy using Automated Reasoning checks to minimize hallucinations.

Optimization feature that intelligently routes prompts to the most cost-effective models while maintaining quality (up to 30% cost reduction).

Data customization tool to securely customize models with proprietary data for personalized AI applications.

Platform capability providing access to hundreds of foundation models from leading AI companies with evaluation tools to select the best model for specific performance and cost needs.

Optimization feature that creates smaller, faster, and cheaper distilled models from larger foundation models with minimal accuracy impact (up to 500% faster, 75% cost reduction).

Tools to evaluate and compare foundation models based on performance and cost metrics to select the best model for specific use cases.

Tools to evaluate and compare foundation models based on performance and cost to select the best model for specific use cases.

Feature that reduces costs and latency by caching prompts for reuse across multiple API calls.

Tools and capabilities for optimizing prompts to improve model performance and accuracy for specific use cases.

Comprehensive enterprise security features including encryption in transit and at rest, identity-based access controls, comprehensive monitoring and logging, and compliance with ISO, SOC, GDPR, FedRAMP High, and HIPAA standards.

Cost optimization feature that automatically routes requests to optimal models, reducing costs by up to 30% while maintaining quality.

A data customization tool that allows organizations to customize models with their own data to move from generic AI to business-specific AI.

Optimization feature that reduces model size and cost (up to 75% cheaper, 500% faster) while maintaining accuracy with minimal impact.

Access to OpenAI frontier models through Amazon Bedrock, expanding model choice for diverse use cases.

Performance optimization feature that reduces latency and costs for repeated prompt inputs.