DealDocs Red-Flag Review (Standard) is a paid API for AI agents from dealdocs.genexxis.com, paid per call via x402, $0.99/call, status unknown (last checked 2026-10-31).
Performs an AI-powered red-flag review of deal documents (term sheets, SAFEs, NDAs, SPAs, etc.) identifying high/medium/low severity issues with clause references, market standards, and suggested fixes from a chosen perspective.
First-pass review of deal documents and financial statements by an AI model with an investment-banking and M&A-lawyer checklist. /redflags: term sheet, SAFE, convertible, shareholders' agreement, LOI, SPA, NDA -> parties, key terms, red flags graded high/medium/low with clause, verbatim quote, market standard (NVCA, BVCA, usual M&A practice) and a concrete fix, missing protections, questions to ask, from the side you choose. /financials: statements in IFRS, US GAAP, French PCG, Moroccan CGNC and others -> normalised JSON per period, plus ratios (margins, leverage, coverage, liquidity, working-capital days, cash conversion) and consistency checks computed in code. Input: text, a URL or a base64 PDF; any language. Documents are never stored.
A structured JSON response containing: document type, identified parties, governing law, key terms with clause references, a list of red flags each graded high/medium/low with verbatim quote, title, clause reference, category, why it matters, market standard, and suggested fix, plus missing protections, questions to ask, and an overall risk rating. Long-running jobs return a poll URL to retrieve results asynchronously.
POSThttps://dealdocs.genexxis.com/redflags?utm_source=zero.xyzUse this endpoint when you need a structured, perspective-aware legal red-flag analysis of a deal document up to 25 pages. Prefer over /redflags/pro for standard-length documents to save cost. Choose this over generic LLM prompting when you need clause-referenced, severity-graded output with market-standard benchmarks and suggested fixes in a consistent JSON schema.
| Field | Type | Description |
|---|---|---|
| url | string | https link to the document (PDF, HTML or plain text) |
| text | string | Document text (min 200 characters). Send exactly one of text, url, pdf_base64. |
| docType | string | Optional hint: auto, term_sheet, safe_or_convertible, shareholders_agreement, loi_or_offer, spa_or_apa, nda |
| language | string | Optional output language: auto, en, fr, es, de, it, pt, nl, ar; default auto (language of the document) |
| pdf_base64 | string | The PDF file, base64-encoded |
| perspective | string | Optional, red flags only: whose side to review for (neutral, investor, founder, company, buyer, seller, lender, borrower, minority_shareholder, majority_shareholder); default neutral |
{
"type": "json",
"example": {
"tier": "std",
"model": "claude-sonnet-5-5",
"counts": {
"low": 1,
"high": 2,
"medium": 3
},
"result": {
"summary": "Series A term sheet, EUR 8m at EUR 24m pre-money with a 15% post-money option pool carved from the pre-money...",
"document": {
"type": "term_sheet",
"parties": [
{
"name": "Acme SAS",
"role": "company"
},
{
"name": "Fund I LP",
"role": "lead investor"
}
],
"governing_law": "French law"
},
"key_terms": [
{
"term": "Liquidation preference",
"value": "2x, participating, uncapped",
"clause": "§5"
}
],
"red_flags": [
{
"quote": "shall receive twice the Original Issue Price ... and shall thereafter participate pro rata",
"title": "2x participating preference",
"clause": "§5",
"category": "economics",
"severity": "high",
"suggested_fix": "Replace with 1x non-participating; if participation stays, cap total return at 3x.",
"why_it_matters": "In a EUR 40m exit the investor takes EUR 16m before sharing the rest.",
"market_standard": "1x non-participating (NVCA/BVCA model terms)"
}
],
"overall_risk": "high",
"questions_to_ask": [
"Is the option pool sized on a hiring plan?"
],
"missing_protections": [
{
"why": "Vesting acceleration and buy-back price are undefined.",
"item": "Founder good-leaver definition"
}
]
},
"status": "done",
"service": "dealdocs",
"analysis": "redflags",
"disclaimer": "Automated first-pass analysis by an AI model. Not legal, accounting, tax or investment advice; may contain errors. Have a qualified professional review before relying on it.",
"perspective": "founder"
}
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