# AWS launches APEX, a shared agentic platform for Wood Mackenzie built on Bedrock AgentCore

Digest AI · Agents & Tools · published 2026-09-17T15:41:03Z · updated 2026-09-18T15:38:53Z

Canonical: https://digestai.news/story/aws-launches-apex-a-shared-agentic-platform-for-wood-mackenzie-built-on-bedrock

## Summary

Wood Mackenzie reports that 88 % of AI proofs‑of‑concept never reach widescale deployment and only about a quarter of enterprises have managed to scale agents beyond pilot projects, according to surveys through early 2026. The main blockers are architectural – lacking evaluation, observability, governance and identity – rather than model quality. To close that gap the company built APEX (Agentic Platform for Energy eXperience), a shared runtime that runs on Amazon Bedrock AgentCore, which reached general availability in October 2025.

APEX provides a managed, model‑agnostic environment that can host any open‑source agent framework (Strands, LangGraph, LangChain, CrewAI, etc.) and any model (Claude, GPT‑4.1, Amazon Nova, Mistral, Llama). It automatically scales from zero to thousands of concurrent invocations, enforces built‑in guardrails and IAM‑based identity, and streams telemetry to CloudWatch. APEX Studio offers a single control‑plane where teams can build, test, deploy and monitor agents without touching underlying infrastructure, cutting development time from months to hours. Consumption‑based pricing charges only active CPU and memory per second, avoiding the idle‑time costs typical of agent workloads.

By standardizing the agent stack, Wood Mackenzie expects teams to focus on business logic rather than re‑creating authentication, memory and observability layers, accelerating the move from experimentation to production and laying groundwork for future multi‑agent systems.

## Key points

- Wood Mackenzie found 88 % of AI PoCs never reach widescale deployment, with only ~25 % of firms scaling agents (2026 surveys).
- APEX, built on Amazon Bedrock AgentCore, offers managed, model‑agnostic runtime, auto‑scaling, guardrails, identity, observability, and a unified control‑plane studio.
- AgentCore’s consumption‑based pricing bills only active CPU/memory per second, eliminating idle‑time costs for agent workloads.

## Why it matters

Standardizing agent infrastructure cuts duplication, speeds production, lowers costs, and enables enterprises to adopt multi‑agent systems at scale.

## Sources

1. [A shared agentic platform for Wood Mackenzie, on Amazon Bedrock AgentCore](https://aws.amazon.com/blogs/machine-learning/a-shared-agentic-platform-for-wood-mackenzie-on-amazon-bedrock-agentcore) (AWS Machine Learning Blog, 2026-09-17, primary source)
2. [Migrating multi-model AI agents to Amazon Bedrock AgentCore runtime](https://aws.amazon.com/blogs/machine-learning/migrating-multi-model-ai-agents-to-amazon-bedrock-agentcore-runtime) (AWS Machine Learning Blog, 2026-09-18, primary source)
3. [The new AgentCore runtime: Elastic, optimized, and consistently fast starts](https://aws.amazon.com/blogs/machine-learning/the-new-agentcore-runtime-elastic-optimized-and-consistently-fast-starts) (AWS Machine Learning Blog, 2026-09-18, primary source)

Part of the developing story: [AWS Optimizes Enterprise AI Infrastructure](https://digestai.news/thread/amazon-sagemaker-hyperpod-introduces-model-caching-to-cut-cold-starts) (10 stories)

## Cite

Digest AI, "AWS launches APEX, a shared agentic platform for Wood Mackenzie built on Bedrock AgentCore", 17 September 2026, https://digestai.news/story/aws-launches-apex-a-shared-agentic-platform-for-wood-mackenzie-built-on-bedrock

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