Hey everyone! I want to learn about the real AI projects people are actually working on these days. There’s so much buzz around AI but I’m curious about what’s actually being built in practice.
I’m especially interested in hearing about:
Automated systems for data processing workflows
Tools that pull information from complicated business databases
Any other practical AI applications you’ve developed
I’m trying to learn from real examples instead of just reading about theory. If you’ve built something cool, could you share what frameworks you used? Things like specific libraries, platforms, or development tools would be super helpful to know about.
Also would love to hear about your development process and any challenges you ran into. Thanks for sharing your experiences!
Last year I automated our customer support ticket routing and it completely transformed our team.
We were drowning in thousands of daily tickets. Agents spent hours just figuring out which department should handle what. My system reads incoming tickets, analyzes content with AI, and auto-routes them to the right team with priority scores.
Here’s the cool part - it doesn’t just categorize. It pulls CRM data, ticket history, and checks our knowledge base to suggest solutions. Sometimes it resolves simple issues without any human help.
The game changer was connecting multiple data sources. Customer database, billing system, product logs, past conversations - everything feeds the decision process. This complex integration used to take months of custom coding.
Now I handle these workflows way faster with visual automation tools. Instead of writing hundreds of lines to connect APIs and databases, I drag and drop components. AI models integrate seamlessly with data processing, and I can modify logic without touching code.
We went from 4 hour average response to 30 minutes. Customer satisfaction jumped 40% in six months.
Anyone looking to build similar automation without the coding headache should check out https://latenode.com
I built an automated invoice processing system for a mid-sized accounting firm that I’m really proud of. It uses OCR and NLP to pull key data from invoices in any format - PDFs, images, even handwritten ones. What makes it special is that it learns from the accounting team’s corrections and gets better over time. I used Python with Tesseract for OCR and spaCy for NLP, plus built a custom training pipeline with scikit-learn. The biggest headache was dealing with wildly different invoice formats from various vendors. Some had tables, others were just text blocks, and many had terrible scan quality. I solved this by creating a preprocessing pipeline that standardizes images and uses template matching to sort invoice types before processing. Now it handles about 85% of invoices automatically with 95% accuracy, saving the firm 20 hours per week. The key was starting with just one client’s invoices and gradually expanding the training data.