Accelerating M&A due diligence with Amazon Bedrock AgentCore

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Mergers and acquisitions (M&A) teams face a persistent challenge: conducting thorough due diligence on multiple acquisition targets while maintaining speed and analytical rigor. Teams often spend weeks manually reviewing targets before identifying viable opportunities. Amazon Bedrock AgentCore is a platform to build, connect, and optimize agents at scale, with any framework or model. It can accelerate this process by orchestrating AI agents that handle data gathering, analysis, and compliance checks autonomously within defined guardrails. In this post, we show how to build a multi-agent due diligence system on Amazon Bedrock AgentCore. We present a reference architecture that combines agent orchestration, knowledge retrieval, and governance controls, then walk through deploying and running the solution using a complete sample repository. The M&A due diligence challenge In transportation and logistics, for example, analysts pull data from financial databases, market research applications, regulatory filings, and internal knowledge bases, then reconcile that information by hand. The process is slow and resource intensive. The problem compounds when teams duplicate work. Industry research, valuation models, and competitive analyses get recreated for each new deal instead of building on institutional knowledge from prior transactions. Meanwhile, governance concerns slow AI adoption because legal and compliance teams require confidence that AI-generated insights are accurate, traceable, and supported by source citations. These four pressures (slow cycles, fragmented data, …

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