dd-agents

Finds what gets buried across hundreds of contracts — cross-references it across 9 specialist domains (Legal, Finance, Commercial, ProductTech, Cybersecurity, HR, Tax, Regulatory, ESG) — and traces every finding to an exact page, section, and quote. Use the structured output alongside your advisors to build IC memos, advisor reports, negotiation checklists, or integration plans.

Battle-tested across multiple completed acquisitions, not just synthetic benchmarks — every quality gate and verification layer below was shaped by what actually broke on real deals.

This tool does not replace professional advisors.Legal, financial, and regulatory conclusions should always be made by qualified professionals. This tool helps your team and advisors work faster.

I built this to solve my own problem. As a corp dev lead, I'd spend weeks assembling the cross-domain picture from siloed advisor reports — legal, financial, and commercial teams all flagging the same subject independently, with nobody connecting the dots. A termination clause in one contract and a revenue concentration risk in the same subject would be flagged in separate workstreams, if at all.

This tool runs all nine workstreams in parallel across every document, cross-references findings automatically, and produces structured analysis your team can search, filter, and drill into — the kind of cross-domain picture that used to take weeks to assemble manually.

Who uses this:Corp dev teams screening targets, PE firms running portfolio DD, legal teams doing contract review, advisors accelerating workstreams. Anyone who needs to search hundreds of contracts and connect findings across domains — it's already run on real acquisitions, not just demo data rooms.

Full Pipeline — Integrated Due Diligence

Analyzes every document through 9 domain lenses, cross-references findings, and validates quality through 5 blocking gates. Produces:

- Interactive HTML report— Go/No-Go verdict with executive narrative, progressive disclosure (decision → actions → domain details → full evidence), severity filtering, and a clause library section that groups findings by canonical clause type (change of control, termination, indemnification, and more) against market-norm comparisons
- 16-sheet Excel report— structured findings, cross-references, audit trail for downstream modeling
- Per-subject JSON findings— every finding with severity, citations, cross-references, and governance graph edges

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

GREEN / YELLOW / RED signal across 8 deal-killer categories. Get a first read before committing to full analysis.

Contract Search — Targeted Questions, No Full Pipeline

dd-agents search prompts.json --data-room ./data_room

Ask specific questions across every contract and get an Excel report with answers, citations, and verification scores. The prompts file is plain JSON any legal professional can write:

dd-agents chat --report _dd/forensic-dd/runs/latest # Interactive multi-turn chat with memory dd-agents query --report _dd/forensic-dd/runs/latest # Ask questions about findings dd-agents cost _dd/forensic-dd/runs/latest # Per-provider / per-model cost rollup dd-agents assess ./data_room # Check data room quality dd-agents portfolio add "Deal A" --data-room ./data_room_a # Track multiple deals dd-agents portfolio compare # Compare risk across deals dd-agents export-pdf report.html # Export to PDF dd-agents log --data-room ./data_room # Browse the deal knowledge timeline dd-agents lineage --data-room ./data_room # Trace finding evolution across runs dd-agents diff run_a/ run_b/ # Compare findings between two run directories dd-agents health --data-room ./data_room # Check knowledge base integrity dd-agents annotate --data-room ./data_room "Confirmed with counsel" # Add analyst notes

Inspect, audit, and tailor each specialist's persona, focus areas, and severity calibration — by editing markdown, not Python. Safety rules can never be removed.

dd-agents agents list # See every specialist and its status dd-agents agents describe --agent legal # Read an agent's persona + safety floor dd-agents agents validate ./my-project # Lint your dd-config/ customizations dd-agents agents preview --agent legal --project-dir ./my-project # Exact assembled prompt

export ANTHROPIC_API_KEY="sk-ant-..."

cp .env.example .env # Edit .env and add your key

export CLAUDE_CODE_USE_BEDROCK=1 export AWS_PROFILE=default export AWS_REGION=us-east-1

Organize contracts into folders by subject or counterparty:

data_room/ SubjectGroup_A/ Acme_Corp/ master_agreement.pdf amendment_2024.pdf Beta_Inc/ license_agreement.pdf SubjectGroup_B/ Gamma_LLC/ services_contract.docx _reference/ # Optional: buyer overview, customer database, etc. buyer_overview.pdf

Supports PDFs, Word, Excel, PowerPoint, and images. Scanned PDFs are handled via OCR.

Data Room (PDFs, Word, Excel, Images) │ ▼ ┌─────────────────────────────────────┐ │ Python Orchestrator │ │ 38-step pipeline │ │ 5 blocking quality gates │ └──────────────┬──────────────────────┘ │ ┌────────────┼────────────┐ │ │ │ ▼ ▼ ▼ ┌──────┐ ┌────────┐ ┌──────────┐ ┌──────────┐ ┌─────────────┐ │Legal │ │Finance │ │Commercial│ │ProductTech│ │Cybersecurity│ │Agent │ │ Agent │ │ Agent │ │ Agent │ │ Agent │ └──┬───┘ └───┬────┘ └────┬─────┘ └────┬─────┘ └──────┬──────┘ │ │ │ │ │ ┌──┴──┐ ┌────────┐ ┌─────┴──────┐ ┌───┴──┐ ┌───────┴─────┐ │ HR │ │ Tax │ │ Regulatory │ │ ESG │ │ + External │ │Agent│ │ Agent │ │ Agent │ │Agent │ │ Agents │ └──┬──┘ └───┬────┘ └──────┬─────┘ └───┬──┘ └───────┬─────┘ │ │ │ │ │ └─────────┴───────┬──────┴────────────┴───────────────┘ │ ┌───────▼────────┐ │ Cross-Domain │ ← Symbolic trigger rules detect │ Analysis │ inter-domain dependencies └───────┬────────┘ │ ┌───────▼────────┐ │ Judge Agent │ ← Validates findings │ (optional) │ └───────┬────────┘ │ ┌───────▼────────┐ │ Merge & Audit │ ← Dedup, numerical checks, │ 31 QA checks │ citation verification └───────┬────────┘ │ ┌───────▼────────┐ │ Executive │ ← Severity calibration, │ Synthesis │ Go/No-Go signal └───────┬────────┘ │ ▼ HTML + Excel + JSON

4 orchestration & synthesis agentsturn raw findings into a decision:

That's13 AI agentsin total. Specialists are config-driven — enable/disable per deal viadeal-config.json— and external specialists can be added via pip entry-points without modifying core code.

Built-in deep-dive lenses (not separate agents):three specialists carry extra focus areas that act as deeper passes within their domain —Insurance(within Finance),Operations(within Commercial), andIP Deep/ freedom-to-operate (within Legal). They surface as their own categories in the report but run inside the parent specialist, so they don't add to the agent count.

The pipelinehalts on quality failuresrather than producing unreliable output. Runs can be resumed from any step.

_dd/forensic-dd/ index/text/ # Extracted document text (cached across runs) inventory/ # File discovery and company registry runs/ latest/ # Always points to the most recent run findings/ legal/ # Per-subject findings from each agent finance/ commercial/ producttech/ merged/ # Deduplicated cross-domain findings report/ dd_report.html # Interactive HTML report dd_report.xlsx # 16-sheet Excel report audit.json # 31 quality validation checks numerical_manifest.json # Every financial figure traced to source metadata.json # Run metadata and API costs knowledge/ # Deal Knowledge Base (compounds across runs) articles/ # Structured knowledge articles chronicle.jsonl # Append-only timeline of all events graph.json # Cross-reference knowledge graph entity_resolution_cache.json # Company name matching (reused across runs)

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