Due Diligence Agents

What does this agent do, and when should you use it?

Due Diligence Agents is an open-source M&A due diligence system driven by the `dd-agents` CLI. It reads an entire data room (PDF, Word, Excel, PowerPoint, images) and analyzes every document through 9 parallel domain specialist agents: Legal, Finance, Commercial, ProductTech, Cybersecurity, HR, Tax, Regulatory, and ESG. A 38-step Python pipeline with 5 blocking quality gates runs cross-domain analysis using symbolic trigger rules, plus 4 orchestration agents including a Judge and an Executive Synthesis agent. Every finding carries severity, an exact page-and-quote citation, and cross-references, producing an interactive HTML report, a 16-sheet Excel report, and per-subject JSON. Analysis runs locally; documents leave your machine only as API calls to your configured LLM endpoint, with no telemetry and a read-only data room. Built by Zohar Babin, the author reports it has been battle-tested across multiple completed acquisitions.

The core flow: dd-agents run deal-config. starts the pipeline, where a Python orchestrator runs 38 steps and 9 domain specialists analyze every data-room document in parallel, each tracing findings to exact page, section, and quote. A cross-domain analysis layer uses symbolic trigger rules to detect inter-domain dependencies (e.g., a termination clause in one contract plus revenue concentration risk on the same subject); an optional Judge agent adversarially spot-checks findings; merge & audit applies dedup, numerical checks, and citation verification across 31 QA checks; an Executive Synthesis agent calibrates severity and emits a Go/No-Go signal. Output lands in {data_room_path}/_dd/forensic-dd/runs/latest/ including report/dd_report.html (interactive report with a clause library and market-norm comparisons), report/dd_report.xlsx (16 sheets), audit., and per-subject JSON. Companion tools: dd-agents search prompts. --data-room ./data_room answers targeted contract questions with citations and verification scores in Excel; --quick-scan gives GREEN/YELLOW/RED triage; and post-run commands include chat, query, cost, portfolio compare, diff, and lineage. Agent personas are customized via dd-config/agents/*.md markdown files with no code changes.

1. A corp dev team screening hundreds of targets runs --quick-scan for a GREEN/YELLOW/RED red-flag signal in minutes before committing to full analysis.
2. A PE firm runs the full pipeline on portfolio targets and uses dd-agents portfolio add and portfolio compare to track and compare risk across deals.
3. A legal team uses dd-agents search with a JSON prompts file to ask specific questions across hundreds of contracts (e.g., is consent required on change of control) and get an Excel report with answers, citations, and verification scores.
4. A deal team preparing an IC memo or negotiation checklist filters findings by severity in the interactive HTML report and verifies each to its exact page and quote.
5. An M&A advisor on a compressed timeline needs the cross-domain risk picture — legal, financial, and commercial flags on the same subject connected — that siloed advisor reports never assemble.

How do you install or deploy this agent?

Prerequisites: Python 3.12+ and an Anthropic API key (or AWS Bedrock, Google Vertex AI, or an Anthropic-compatible gateway).

Recommended install (includes PDF extraction):
bash

pip install 'dd-agents[pdf]'

Alternatives:
bash

brew install zoharbabin/due-diligence-agents/dd-agents
docker pull zoharbabin/due-diligence-agents:latest
pip install dd-agents              # core only (no PDF extraction)
pip install 'dd-agents[vector]'    # + ChromaDB semantic search
pip install 'dd-agents[ocr]'       # + OCR for scanned docs (English)

Note: the optional [pdf] extra installs pymupdf, which is AGPL-3.0 licensed — if you redistribute software bundling pymupdf, AGPL copyleft terms apply.

How do you use this agent?

Set your key and run:
bash

export ANTHROPIC_API_KEY="sk-ant-..."
dd-agents auto-config "Buyer Corp" "Target Inc" --data-room ./data_room

dd-agents doctor --config deal-config.
dd-agents run deal-config.

Results appear at {data_room_path}/_dd/forensic-dd/runs/latest/report/dd_report.html — open it in your browser.

Quick triage without the full pipeline:
bash

dd-agents run deal-config. --quick-scan --model-profile economy

Generate a config without any API calls:
bash

dd-agents init --data-room ./data_room

Organize the data room into folders by subject or counterparty; PDFs, Word, Excel, PowerPoint, and images are supported, with OCR for scanned PDFs. The minimal config requires config_version, buyer.name, target.name, deal.type, deal.focus_areas, and data_room.path.

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