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DD-Agents — Forensic M&A Due Diligence

Legal flags a risk. Finance flags another. We connect and cite. Open-source forensic M&A due diligence — 13 AI agents read your entire data room across 9 specialist domains, cross-reference the findings no single reviewer connects, and trace every one to an exact page and verbatim quote. Quality-gated HTML + Excel reports.

Quick Start

pip install dd-agents[pdf]
export ANTHROPIC_API_KEY="sk-ant-..."
dd-agents init --data-room ./your_data_room
dd-agents run deal-config.json

See a sample report →

What It Does

Command Purpose
dd-agents run Full 38-step pipeline across 9 domains
dd-agents run --quick-scan Adds a red-flag stoplight triage pass to the run
dd-agents search Targeted contract questions with citations
dd-agents chat Interactive multi-turn chat about findings
dd-agents query Single-question mode
dd-agents assess Data room quality check

What dd-agents does (and does not) do

dd-agents is a forensic analysis accelerator for M&A due diligence — it gets your team and advisors to the connected picture faster, with every claim traceable to the source.

It does:

  • Read an entire data room across 9 domains and cross-reference findings no single-domain reviewer connects.
  • Trace every finding to an exact page and verbatim quote, so each conclusion is auditable.
  • Halt rather than ship unverified output — quality gates are fail-closed, not advisory.
  • Run locally: documents only leave your machine as API calls to your own LLM provider — Anthropic API, AWS Bedrock, or Google Vertex AI, or any model (GPT, Gemini, …) via an Anthropic-compatible gateway. Your choice, via env config; see Model Providers.
  • Produce structured output (interactive HTML, Excel, JSON) you use as a basis for IC memos, advisor reports, and negotiation checklists.

It does not:

  • Replace qualified legal, financial, tax, or regulatory advisors — it accelerates them; humans make the conclusions.
  • Operate without human oversight, or claim to be a final, sign-off-ready deliverable.
  • Guarantee a model never errs — the value is that findings are cited and checkable, and the pipeline stops rather than emit a claim it cannot ground.
  • Send your data room anywhere beyond your configured LLM provider, or store credentials in its output.

Install Options

pip install dd-agents[pdf]

pipx install dd-agents[pdf]

brew install zoharbabin/due-diligence-agents/dd-agents

docker pull zoharbabin/due-diligence-agents:latest
docker run -e ANTHROPIC_API_KEY="$ANTHROPIC_API_KEY" \
  -v ./data_room:/data zoharbabin/due-diligence-agents run /data/deal-config.json

Next Steps