Feature · AI Summarization
The point of a document shouldn't require reading the whole document.
Extract structured metadata from any document. Title, language, abstract, topics, named entities, sentiment — returned as clean JSON.
Try free — 40 creditsOutput format
Structured output, not a text block
Every summary returns a consistent JSON structure — no prompt engineering, no parsing.
{
"title": "Q3 Financial Report",
"language": "en",
"word_count": 4820,
"abstract": "Revenue grew 12% YoY to $4.2B in Q3...",
"key_topics": ["revenue", "EBITDA", "forecast"],
"named_entities": ["Acme Corp", "Q3 2024"],
"sentiment": "neutral"
}Where summarization saves hours
Contract Review
40-page contract → key obligations, parties, dates, renewal clauses, and liability caps extracted in one call.
Financial Reports
Earnings PDF → structured financial metrics: revenue, EBITDA, guidance, risk factors. Ready for CRM or dashboard.
Incident Reports
Compliance documents → key facts, dates, parties, and severity for audit trail without manual reading.
Email Attachments
Incoming PDFs from customers → CRM property updates automatically. Opportunities updated without human triage.
Works with your AI stack
The structured JSON output from Parselane feeds into any LLM provider. No custom parsing needed.
API example
curl -X POST https://api.parselane.com/v1/process \ -H "Authorization: Bearer YOUR_API_KEY" \ -F "file=@report.pdf" \ -F "action=summarize" \ -F "include_entities=true" \ -F "include_sentiment=true"
Turn any document into structured data. One credit.
40 free credits. No card required. Structured JSON output compatible with any LLM or automation platform.