Accelerate Enterprise AI Development using Weights & Biases and Amazon Bedrock AgentCore

Why it matters (2 min)

• This post is co-written by Thomas Capelle and Ray Strickland from Weights & Biases (W&B).
• Generative artificial intelligence (AI) adoption is accelerating across enterprises, evolving from simple foundation model interactions to sophisticated agentic workflows.
• Open receipts to verify and go deeper.

Go deeper (8 min)

Context

This post is co-written by Thomas Capelle and Ray Strickland from Weights & Biases (W&B). Generative artificial intelligence (AI) adoption is accelerating across enterprises, evolving from simple foundation model interactions to sophisticated agentic workflows. As organizations transition from proof-of-concepts to production deployments, they require robust tools for development, evaluation, and monitoring of AI applications at scale. In this post, we demonstrate how to use Foundation Models (FMs) from Amazon Bedrock and the newly launched Amazon Bedrock AgentCore alongside W&B Weave to help build, evaluate, and monitor enterprise AI solutions. We cover the complete development lifecycle from tracking individual FM calls to monitoring complex agent workflows in production. Overview of W&B Weave Weights & Biases (W&B) is an AI developer system that provides comprehensive tools for training models, fine-tuning, and leveraging foundation models for enterprises of all sizes across various industries. W&B Weave offers a unified suite of developer tools to support every stage of your agentic AI workflows. It enables: Tracing & monitoring: Track large language model (LLM) calls and…

For builders

Builder: read docs/changelog; watch for breaking changes, quotas, and pricing.

Verify

Prefer primary announcements, papers, repos, and changelogs over reposts.

Receipts

1. Accelerate Enterprise AI Development using Weights & Biases and Amazon Bedrock AgentCore (AWS Machine Learning Blog)