Generative AI with Amazon Bedrock

Enterprise-grade GenAI applications with foundation models, RAG architectures, AI agents, and responsible AI guardrails.

RAG Architecture Pattern

Retrieval-Augmented Generation combining enterprise knowledge with foundation model capabilities for accurate, contextual responses.

// Data Ingestion Pipeline
Documents (S3) → Bedrock Knowledge Base
  → Chunking (semantic/fixed)
  → Embedding (Titan/Cohere)
  → Vector Store (OpenSearch Serverless)
// Query Pipeline
User Query → Embedding → Vector Search
  → Context Assembly → Foundation Model
  → Guardrails → Response
Bedrock KB OpenSearch Titan Embeddings

Bedrock Agents & Orchestration

Autonomous AI agents that reason, plan, and execute multi-step tasks using tools, APIs, and knowledge bases.

Agent Capabilities:

  • • Action groups (Lambda functions as tools)
  • • Knowledge base retrieval
  • • Multi-step reasoning & planning
  • • Session memory & context tracking
  • • Return of control for human-in-the-loop
  • • Guardrails for content filtering
Agents Guardrails Claude

Foundation Models

Access to leading foundation models through a unified API with enterprise security, privacy, and compliance.

Claude 3.5
Anthropic
Titan
Amazon
Llama 3
Meta
Mistral
Mistral AI

Model evaluation, fine-tuning, and custom model import available through Bedrock.

Enterprise GenAI Use Cases

Intelligent Document Processing

Extract, summarize, and classify documents at scale

Conversational AI Assistants

Customer support bots with domain-specific knowledge

Code Generation & Review

AI-assisted development with CodeWhisperer + Bedrock

Content Personalization

Dynamic content generation for marketing & e-commerce

Machine Learning with SageMaker

End-to-end ML platform for building, training, and deploying models at scale with MLOps best practices.

SageMaker Studio

  • • Unified IDE for ML development
  • • JupyterLab & Code Editor
  • • Data Wrangler for prep
  • • Autopilot for AutoML
  • • Canvas for no-code ML

Training & Optimization

  • • Distributed training (data/model parallel)
  • • SageMaker Training Compiler
  • • Spot Training for 90% savings
  • • Hyperparameter tuning
  • • Built-in algorithms (XGBoost, etc.)

MLOps & Deployment

  • • SageMaker Pipelines (CI/CD for ML)
  • • Model Registry & versioning
  • • Real-time & batch inference
  • • Multi-model endpoints
  • • Model Monitor for drift detection

Modern Data Platform on AWS

Unified data lake and warehouse architecture with Lake Formation governance, Glue ETL, and analytics with Athena and Redshift.

Data Lake Architecture

// Zones
S3 Raw Zone → S3 Curated Zone → S3 Analytics Zone
// Governance
Lake Formation: Catalog | Permissions | Column-level security
// Processing
Glue Crawlers → Glue ETL (Spark) → Glue Data Quality
// Query
Athena (ad-hoc) | Redshift Spectrum | EMR (big data)
Lake Formation Glue Athena

Real-Time Streaming

// Ingestion
IoT/Apps → Kinesis Data Streams (shards)
→ Kinesis Data Firehose (delivery)
// Processing
Managed Apache Flink → windowed aggregations
→ anomaly detection → enrichment
// Output
→ OpenSearch (dashboards) | S3 (lake) | Redshift
Kinesis Flink Firehose

Amazon Redshift

Petabyte-scale warehouse with Serverless, zero-ETL from Aurora, and data sharing.

AWS Glue

Serverless ETL with Spark, crawlers, Data Catalog, and Data Quality rules.

Amazon Athena

Serverless SQL queries on S3. Federated queries across 25+ data sources.

Amazon QuickSight

Serverless BI with SPICE engine, ML insights, and embedded analytics.

Amazon Kinesis

Real-time data streaming with Data Streams, Firehose, and Video Streams.

Lake Formation

Centralized governance with fine-grained access control and data sharing.

Apache Flink (Managed)

Stateful stream processing for real-time analytics, CEP, and ETL.

AWS DMS

Database migration with CDC for ongoing replication and schema conversion.

Ready to Build with GenAI?

Start with a free GenAI workshop. We'll help you identify high-value use cases and build your first Bedrock application.