Fine-Tuning vs RAG on AWS Bedrock: When to Use Each
Compare fine-tuning and RAG (retrieval-augmented generation) for customizing LLMs on Bedrock. Cost, latency, and accuracy trade-offs.
Compare fine-tuning and RAG (retrieval-augmented generation) for customizing LLMs on Bedrock. Cost, latency, and accuracy trade-offs.
Production guide for HIPAA-compliant generative AI on AWS Bedrock — BAA scope, eligible models, Guardrails for PHI redaction, Knowledge Bases for RAG over clinical data, VPC isolation, and the audit evidence package OCR investigators expect.
Build SaaS with AI: multi-tenant architecture on Bedrock, cost isolation, and tenant data security.
The 20 AWS services reshaping enterprise architecture in 2024–2026: AI agents, vector storage, generative BI, distributed SQL, and security automation explained.
Amazon Bedrock Agents automate workflows by giving foundation models the ability to call tools (APIs, Lambda, databases). This guide covers building agents with tool definitions, testing in the console, handling errors, and scaling to production.
Amazon Bedrock Knowledge Bases automate the RAG (Retrieval-Augmented Generation) pipeline — semantic search, chunking, embedding, and context injection into Claude or other foundation models. This guide covers setup, data ingestion, cost optimization, and production patterns.
Amazon Bedrock Guardrails protect foundation models from harmful outputs — filtering on prompt injection, jailbreaks, toxicity, and PII. This guide covers setup, testing, cost optimization, and production safety patterns for GenAI applications.
Bedrock billing is not a single line item — it is a composition of model invocation costs, Knowledge Base retrieval, Agent orchestration, Guardrails evaluation, and cross-region inference profile routing. Each component has its own pricing model and its own set of cost traps.
Nova Forge SDK, Lambda Durable Functions, Graviton5, Trainium3 UltraServers, Route 53 Global Resolver GA, and more — the AWS announcements that actually matter from March 2026.
Amazon Bedrock AgentCore solves the production gaps in Bedrock Agents API: persistent memory, tool reliability, and agent observability. Here is the architecture guide.
Build multi-step AI pipelines visually with Amazon Bedrock Flows. We compare it to Step Functions and custom Lambda orchestration with a decision matrix for enterprise teams.
Amazon Bedrock Data Automation replaces fragmented Textract + Comprehend + Lambda pipelines with a managed intelligent document processing service. Production guide.