中文
ProFinance6 nodes
Score 77

Invoice Processing Automation

Upload any-format invoices — 7-node pipeline auto-completes OCR, field extraction, amount validation, compliance check, and multi-source reconciliation into one Excel workbook.

What does this workflow do?

图像质量预检与增强(去倾斜/降噪/对比度)→ 多引擎 OCR 识别(PaddleOCR)→ NLP 字段语义提取 → 金额大小写交叉校验 → 税号格式与日期合理性检查 → 多源数据自动对账匹配 → 异常交易智能标记与分级告警 → 多 Sheet Excel 报告(明细/汇总/对账结果/异常清单)

System flow

图像质量预检与增强(去倾斜/降噪/对比度)→ 多引擎 OCR 识别(PaddleOCR)→ NLP 字段语义提取 → 金额大小写交叉校验 → 税号格式与日期合理性检查 → 多源数据自动对账匹配 → 异常交易智能标记与分级告警 → 多 Sheet Excel 报告(明细/汇总/对账结果/异常清单)

Pipeline breakdown

PaddleOCR image Pillow image LLM Reasoning json Pandas json LLM Reasoning json OpenPyXL json
  1. PaddleOCR paddleocr — High-accuracy OCR that reads text, tables and stamps from scans and photos image → json
  2. Pillow pillow — Image pre-processing — deskew, denoise, crop and normalise before analysis image → image
  3. LLM Reasoning llm — Large-language-model step that extracts, classifies, validates or writes structured output json → json
  4. Pandas pandas — Tabular compute — join, aggregate, validate and reshape the extracted records json → json
  5. LLM Reasoning llm — Large-language-model step that extracts, classifies, validates or writes structured output json → json
  6. OpenPyXL openpyxl — Writes a formatted, formula-ready Excel workbook as the deliverable json → xlsx

Workflow Reputation Score

Based on executions, success rate, update frequency, component quality, and user rating.

77Overall
★★★★ 4.5
Executions
30
Success rate
100
Update frequency
85
Component quality
93
User rating
90

Based on executions, success rate, update frequency, component quality, and user rating.

Components used

PaddleOCRpaddleocr

High-accuracy OCR that reads text, tables and stamps from scans and photos

PaddlePaddle/PaddleOCR ↗
Pillowpillow

Image pre-processing — deskew, denoise, crop and normalise before analysis

python-pillow/Pillow ↗
LLM Reasoningllm

Large-language-model step that extracts, classifies, validates or writes structured output

FlowSync proprietary
Pandaspandas

Tabular compute — join, aggregate, validate and reshape the extracted records

pandas-dev/pandas ↗
OpenPyXLopenpyxl

Writes a formatted, formula-ready Excel workbook as the deliverable

theorchard/openpyxl ↗

How is this different from n8n or Zapier?

Unlike generic workflow builders, FlowSync workflows ship pre-configured with AI skills baked into every node — OCR, LLM reasoning, transcription, super-resolution — not just webhook triggers. Each node is white-box auditable: you see input, output, and config. Deployment is instant — no self-hosting, no API-key per node.

Use cases

  • 企业财务月度对账
  • 审计材料批量预审
  • 费用报销合规检查
  • 多公司并表数据合并

Author & Source

This workflow is maintained by the FlowSync team. All components are open-source or commercially licensed. Source code for each component is linked in the Components section above.

Pricing: Free tier available · 30% commission on forks · PRO tier · Official

Field notes

每月 2000+ 张发票录入,以前 3 人做一周。现在 1 人 2 小时。金额一致性校验零差错。

— 财务总监 陈, 集团财务总监

多个客户的数据汇总到一张表,异常自动标红。客户满意度直接拉满。

— 代账公司 李, 代账公司负责人

合规检查模块节省了大量初步审核时间,异常标记的逻辑非常专业。

— 审计师 Jane, 四大审计经理

Data handling

发票数据仅在处理链路中临时使用,不存储原始扫描件。提取的财务数据加密存储于您的账户。支持处理完成后一键清除全部数据。

FlowSync Workflow Marketplace · 77 reputation score · 30% execution · 100% success · 6-node white-box pipeline · maintained by FlowSync Official

Ready to run?

Upload any-format invoices — 7-node pipeline auto-completes OCR, field extraction, amount validation, compliance check, and multi-source reconciliation into one Excel workbook.