Automated AI Document Extraction & Classification Pipeline Built a fully automated document proce...

Automated AI Document Extraction & Classification Pipeline Built a fully automated document proce...Automated AI Document Extraction & Classification Pipeline Built a fully automated document proce...

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Aakash Aggarwal

• Jan 7

Automated AI Document Extraction & Classification Pipeline

Built a fully automated document processing pipeline to replace manual review and data entry of logistics documents such as invoices and bills. The system ingested uploaded documents, stored them in object storage, and triggered asynchronous AI workflows via message queues to extract required fields, classify document types, and persist structured outputs directly into the database.

The pipeline was designed for high throughput and reliability, eliminating human intervention entirely and significantly accelerating business operations by turning unstructured documents into validated, structured data at scale.

Backend Development AI Engineer Claude FastAPI Python

Maxmus studio

• Sep 28

Building AI for healthcare leaves zero room for error.

I’m currently collaborating with an incredible team on Raphald AI, a medical detection application. Building the systems for a project with stakes this high is a massive reminder that the underlying backend architecture matters just as much as the machine learning model itself.

When integrating diagnostic AI, your API endpoints cannot drop requests, and your database workflows demand absolute integrity. You aren't just passing JSON payloads; you are handling critical, real-time workflows where stability is non-negotiable.

Engineering these systems continues to shape my approach to building robust Python backends. If you are developing a product that requires reliable AI integration or rock-solid FastAPI infrastructure, check out the newly updated services on my profile. Let's build something that works when it counts.