I’m excited to share some good news today: after a period of technical refinement, Aiefficiency’s core product — a multilingual AI document processing assistant built on the n8n workflow engine — has completed its build and testing in a local environment, and the results have exceeded expectations.
The system is currently in the server deployment and launch preparation phase, and it will take a little more time before it’s officially open to all users. This article wants to share with you our original motivation, our approach to technology selection, the capabilities we have already validated, and our future plans. If you also struggle with multilingual document processing efficiency, feel free to follow us — we’ll notify you as soon as the product launches.
I. Why We Started This Project
Anyone working in cross-border business probably feels the same: you’re drowning in documents in different languages every day.
Quotes in Japanese, invoices in English, customer emails in Spanish, supplier contracts in German… each one takes time to translate, extract key information from, and organize for archiving. These may seem like small tasks, but over the course of a day, 30% of working time gets eaten up by this repetitive work.
Of course there are translation tools and various SaaS products on the market, but there are always a few pain points that don’t get solved:
❌ Data insecurity: Contracts, quotes, and customer information uploaded to third-party platforms — you never know how long they’ll be retained or whether they’ll be used for model training
❌ Too generic: General translation tools can only translate sentence by sentence; they won’t automatically extract the amounts, dates, and clauses you actually need
❌ Fragmented workflow: Translation is one tool, OCR is another, and spreadsheet organization is yet another — switching back and forth makes you even less efficient
❌ Opaque pricing: Charging by page, by word count, by monthly membership — you can’t clearly track usage, and the bill always comes as a surprise
So we decided to build our own — an AI automation solution that is secure and controllable, ready to use out of the box, focused on document processing, and with zero data retention.
II. Technology Selection: n8n + Ngrok + Gemini
We compared several solutions and ultimately chose the combination below, which we have already fully validated locally:
Component
Role
Selection Reason
n8n
Workflow orchestration engine
Open source, visual drag-and-drop, 600+ nodes, extremely strong extensibility — no need to rebuild when adding features in the future
Gemini
AI multimodal processing core
Leading multilingual capabilities, high OCR accuracy, good structured extraction results — free tier is sufficient for the validation phase
Ngrok
Secure tunneling service
Simple configuration, HTTPS encryption, stable and reliable — suitable for public network access during development and testing phases
Why n8n instead of pure code?
The answer is simple: maintainability. If you write a backend from scratch in Python, every new feature later requires code changes, database changes, and API changes — iteration speed is very slow. With n8n’s visual workflows, adding a new capability (like email notifications, spreadsheet writing, or knowledge base retrieval) often just means dragging in a new node and getting it done in ten minutes.
For a product like document processing that requires continuous iteration, n8n’s flexibility lets us quickly respond to user needs instead of being constrained by our tech stack.
III. Validated Core Capabilities
From testing in the local environment, all of the following capabilities have been fully implemented with stable results:
✅ Multi-format file support
PDF (text/scanned), Word (.doc/.docx), Excel, images (JPG/PNG), and plain text files — all can be uploaded and automatically recognized and processed.
✅ 30+ languages automatic recognition and translation
Automatic detection and translation for major languages including Chinese, English, Japanese, Korean, French, German, Spanish, Russian, Portuguese, Italian, etc. Professional term accuracy reached over 95% in test samples.
✅ Structured information extraction
It’s not just translation — it can also automatically extract key information according to your needs and output it in JSON format:
Document type classification (quote/invoice/contract/email/report/other)
Amount extraction (including currency recognition)
Date extraction
Institution/company name extraction
Contact information extraction
Core clause summary
Custom field extraction (can be customized by industry)
✅ Intelligent summarization
Supports generating document summaries by length options (100/300/500 words), quickly grasping key points from long documents.
✅ Zero data retention
Files are only processed in memory and released immediately after processing — no disk writes, no execution logs retained, no uploads to third-party storage. We have repeatedly verified this: after processing completes, no trace of user files can be found on the server.
IV. Real Test Results from Local Environment
Here are a few examples that impressed us during testing:
Example 1: Japanese quote PDF
A 12-page construction engineering quote in Japanese — results returned 9 seconds after upload. Not only was it fully translated into Chinese, but 12 key items were also automatically extracted and organized into a structured table: total amount (JPY), quote validity period, supplier name, payment terms, delivery cycle, etc. This was at least 20 times faster than manual processing.
Example 2: Handwritten English invoice photo
A slightly blurry photo taken with a phone of a handwritten English invoice — OCR recognition accuracy was 97%. It automatically extracted the invoice number, billing date, customer name, total amount, and tax amount, even correctly recognizing the messy handwritten signature.
Example 3: Spanish customer complaint email
A long email in Spanish — the system automatically judged the sentiment as “negative complaint”, extracted complaint points, customer demands, and order number, and generated a Chinese reply suggestion.
These test results gave us more confidence: this solution really can help professionals save a lot of time.
V. What’s Next
Completing local validation is just the first step. Next, we’ll move forward according to this roadmap:
🔹 Step 1: Cloud server deployment (in progress)
We are currently selecting and configuring cloud servers to migrate the n8n workflow engine from local to the cloud, enabling 24/7 stable operation. We will also configure production-grade infrastructure such as enterprise-grade secure tunnels, load balancing, and automatic backups.
🔹 Step 2: Frontend user interface optimization
Currently we’re using a minimal upload interface for testing. Before official launch, we’ll fully polish the Aiefficiency website’s upload interaction, result display, and user system to ensure it works well on both mobile and desktop.
🔹 Step 3: Stress testing and security audit
We’ll simulate system performance under different concurrency levels to ensure stable operation. At the same time, we’ll conduct a complete security audit to verify the reliability of the zero-retention mechanism.
🔹 Step 4: Closed beta invitations
Before launch, we’ll open a limited number of beta spots, inviting friends with real document processing needs to experience it early, collecting feedback before the official release.
🔹 Step 5: Continuous iteration of more capabilities
Launch is just the beginning. Going forward, we’ll gradually add:
Batch document processing
Email-triggered automatic processing
Multi-format export (Word/Excel/PDF)
Team collaboration and sharing
Industry-specific workflow templates
Closing Words
Many people ask me: there are already so many AI products made by big companies on the market — is there any point in you building this?
My answer is: Yes, there is. Because one-size-fits-all products can never replace small, focused vertical solutions.
We don’t build general-purpose large models, we don’t build chatbots, we don’t chase trends. We only focus on one thing — using n8n + AI to help professionals perfect the small but important task of document processing: making it secure enough, fast enough, and easy enough to use.
If you also struggle with multilingual documents every day, we welcome you to follow Aiefficiency. You’ll be the first to know when the product officially launches.
Of course, if you have specific document processing scenarios, or if you want to participate in the early beta, feel free to leave a comment. We’ll prioritize users with real needs.
We have to take it step by step, but we’re heading in the right direction.
Stay tuned.