Multilingual Partner Onboarding
Automating complex, multi-language data entry to cut onboarding time from 4 hours to <5 minutes using n8n and Vision OCR.
Automation Architect & Developer
Timeline
5 Weeks (Dev & Testing)
n8n, Python, Vision OCR, Node.js, Render
Zero Manual Data Entry
Challenge
Our post-sales handoff was a major bottleneck. Onboarding a new partner involved manually entering data from contracts into multiple internal systems.
Complexity: Contracts came in over 10 different languages, making manual extraction slow and error-prone.
Inconsistency: different regions had different data requirements, leading to "dirty data" entering our systems.
Time Sink: It took up to 4 hours of operational effort just to get a partner "system ready."
Results
I built a "zero-touch" automation pipeline that handles the entire process without human intervention.
Intelligent Extraction: I wrote a Python script utilizing Vision OCR to read PDF contracts and extract key partner details, regardless of the language.
Robotic Process Automation (RPA): Developed a Node.js bot that takes the clean data and auto-fills our internal admin panels, mimicking human input but at machine speed.
AI Fallback: Integrated Claude and Gemini to handle edge cases or unclear document scans.
< 5 Mins
Process Time (Down from 4 Hours)
100%
Manual Entry Eliminated
12+
Languages Supported
Process
Pattern Recognition: Analyzed contracts from 10+ regions to map common data fields and identify language-specific variations.
OCR Tuning: configured Vision OCR and wrote Python regex scripts to accurately target and extract specific entities (like Tax IDs and Address blocks) from non-English text.
Bot Logic: Built the Node.js script to navigate our internal legacy systems, handling login, navigation, and form submission automatically.
Orchestration: Wired the entire flow in n8n, creating a seamless trigger that kicks off technical integration the moment the contract is processed.
