
Amazon Bedrock Data Automation: Intelligent Document and Media Processing at Scale
Amazon Bedrock Data Automation replaces fragmented Textract + Comprehend + Lambda pipelines with a managed intelligent document processing service. Production guide.
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Amazon Bedrock Data Automation replaces fragmented Textract + Comprehend + Lambda pipelines with a managed intelligent document processing service. Production guide.

On June 16, 2026, S3 Vectors raised the QueryVectors limit to 10,000 results per query and cut data-processed charges up to 80% on indexes over 10M vectors. Architecture, pagination, and cost comparison vs OpenSearch and MemoryDB.

Deploying GenAI without guardrails is a compliance incident waiting to happen. Here is how to build a production-grade AI governance layer on AWS using Amazon Bedrock Guardrails, least-privilege IAM, and continuous evaluation.

One AWS contract, multiple foundation models. Learn how to procure, govern, and cost-optimize Meta Llama, Mistral, Cohere, and more via Amazon Bedrock Marketplace.

July 2026: Trainium2 (trn2.48xlarge, 3.2 Tbps EFA) and Inferentia2 via Neuron SDK — AWS cites ~30-40% better price performance vs P5e/P5en; measure your workload before quoting wider savings.

July 2026: Nova Canvas (images) and Nova Reel 1.1 (video up to 2 minutes in 6s shots on Bedrock) — Guardrails, C2PA, async pipelines, and a production checklist. Confirm model lifecycle before locking UX.

Your CISO blocks ChatGPT Enterprise. Your engineering team prefers it. A CTO-level decision framework for picking between Amazon Q for Business and ChatGPT Enterprise — data residency, per-seat economics, and the integrations that decide which one actually ships.

Studio Classic isn't going away today, but the new feature work isn't going there. A migration playbook for enterprise ML teams moving to SageMaker Unified Studio — what breaks, what gets easier, and the IAM permissions that catch every team off-guard on day one.

Building generative AI on AWS? Amazon Bedrock removes the complexity of training and hosting foundation models, letting businesses deploy production LLM apps faster, more securely, and at lower cost.