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Screen an M&A target with cited DCF and prior deals
Run screening, DCF/comparable valuation, strategic fit, and citation checks for a synthetic logistics target; deliver a transaction diligence report.
Goal
Create diligence material for a simulated acquisition with cited numbers, prior-deal context, and unresolved questions.
Steps
- Start the sample Bedrock AgentCore workspace and confirm target/deal data is marked SYNTHETIC DATA. [src10-aws-screen-synthetic-ma-target-with-cited-dcf-and-prior-deals]
- Route target-screening questions to Target Screening, valuation assumptions to Financial Analysis, and prior-deal context to Strategic Fit. [src10-aws-screen-synthetic-ma-target-with-cited-dcf-and-prior-deals]
- Have Compliance Validation check every numeric citation and governance checklist, then produce a report with sources, sensitivities, and open items. [src10-aws-screen-synthetic-ma-target-with-cited-dcf-and-prior-deals]
How to verify
Check DCF inputs against Knowledge Base citations, verify strategic-fit references prior_deals, and ensure uncited claims are flagged rather than invented.
Troubleshooting
For an uncited number, inspect financial-tool/KB output; for no target, check the synthetic Aurora table and do not connect real deal data.
Permissions
Prerequisites
- AWS test account, Bedrock AgentCore permissions, synthetic Aurora/S3 data, and enabled sample models.
Permissions
- Deployment creates AWS networking, database, AgentCore, CloudWatch, and X-Ray resources and incurs costs; the data is synthetic.
Limitations
The sample is not valuation advice or real transaction diligence; DCF, multiples, and precedents are demonstrative.
Pinned upstream source
- Repository
- aws-samples/sample-ma-due-diligence-agentcore
- File path
- README.md
- Pinned commit
3d6191a9c3ac6eae2b31b66dd4f72e11077ee8a2- Source checked
- 2026-10-14 · Reviewed against the pinned upstream source
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License: MIT-0
Main topic
Turn ecommerce campaign materials into a reviewable weekly brief