Automate Data Extraction In Seconds
AI extracts structured data from any document — invoices, emails, PDFs, forms — and pushes it to your systems. Replace $15/document manual entry with $0.08/page automation.
Free forever (30 pages/mo). Set up in under 2 minutes.
EXTRACTING FIELDS FROM INVOICE...
Trusted by teams replacing manual data entry in logistics, finance, and operations
6+ hrs
Saved Per Week
<3s
To Process Any Document
$40K+
Saved Per Year (100 docs/day)
99%
More Accurate Than Manual
Manual data entry is costing you more than you think
Every document processed by hand costs $15-25 in labor, errors, and delays.
Your team spends hours per day typing data from invoices and documents into spreadsheets — that's $40K+/year in hidden labor costs
Manual entry has a 1-4% error rate per field — multiply that across hundreds of documents and errors compound into real revenue loss
Legacy OCR and template-based tools need per-format configuration, break when layouts change, and still require manual review
Automate extraction in 3 steps
Step 1
Send Documents to Parsli
Upload PDFs and images, forward emails, or send documents via REST API or webhook. Any ingestion method works.
Step 2
AI Extracts Your Data
Define the fields you need — amounts, dates, vendor names, line items — and the AI extracts them from any document format automatically.
Step 3
Data Flows to Your Systems
Structured data pushes to your ERP, CRM, accounting software, or spreadsheets via Zapier, Make, webhooks, or API.
See how teams automate extraction
Click through the full workflow — from uploading a document to structured data flowing into your systems. Takes 60 seconds.
No credit card required. Cancel anytime.
What our customers say
“We replaced 3 hours of daily invoice data entry with a fully automated pipeline. Parsli paid for itself in the first week.”
Sarah M.
Operations Manager, Logistics Company
“Our team used to manually key in 200+ documents per week. Now the AI handles it in minutes — more accurate than we ever were.”
David R.
AP Lead, Distribution Company
Why teams replace manual entry with Parsli
AI-Powered Extraction
Google Gemini 2.5 Pro reads documents like a human — understanding context, tables, and relationships. No templates or rules needed.
Any Document, Any Format
Invoices, POs, receipts, BOLs, forms, bank statements — PDFs, images, emails, Word, Excel. If it has data, Parsli extracts it.
5,000+ Integrations
Push extracted data to Google Sheets, your ERP, CRM, or any app via Zapier, Make, webhooks, or REST API.
Manual entry vs. Parsli automation
Based on processing 100 documents per month.
| Feature | Others | Parsli |
|---|---|---|
| Cost per document | $15-25 (manual labor) | $0.08/page (AI) |
| Processing time | 10-15 min each | < 3 seconds |
| Error rate | 1-4% per field | < 1% |
| Monthly cost (100 docs) | $1,500-2,500 | $20 |
| Scale capacity | Limited by headcount | Unlimited |
| Setup time | N/A (ongoing labor) | 2 minutes |
No credit card required. Cancel anytime.
Frequently asked questions
Stop paying $15 per document for data entry
Join hundreds of teams automating extraction with AI. Free forever up to 30 pages/month.
No credit card required. Cancel anytime.
“We replaced 3 hours of daily invoice data entry with a fully automated pipeline. Parsli paid for its...”— Sarah M., Logistics Company
The True Cost of Manual Data Entry
According to research by the Association for Intelligent Information Management (AIIM), organizations spend an average of $20 in labor to file a single document, and $120 to find a misfiled one. When factoring in error correction, manual data entry costs $15-25 per document across industries.
A McKinsey Global Institute study (2023) found that 60-70% of employee time is spent on data collection, data processing, and data entry tasks that are automatable with current AI technology. For a team processing 100 documents per day, that translates to $40,000-$60,000/year in labor costs that AI extraction can eliminate.
The manual data entry error rate is typically 1-4% per field according to research published in the International Journal of Industrial Ergonomics. At scale, these errors compound: a 2% error rate across 10 fields per document means 18% of documents contain at least one mistake. AI-powered extraction achieves sub-1% error rates by understanding document context rather than relying on keystroke accuracy.
The intelligent document processing market is projected to grow from $1.45 billion (2022) to $12.81 billion by 2030 (source: Fortune Business Insights), driven by organizations replacing manual entry with AI-powered automation.