I will build a multimodal document ai and ocr data extraction pipeline

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claude_devs
Muhammad T.
Alcune informazioni sono riportate in lingua inglese.

Informazioni su questo servizio

Are you spending hours manually retyping invoices, medical claims, bank statements, or messy scanned forms into your software?

I will build an enterprise-grade Multimodal Document AI and OCR data extraction pipeline that converts complex, unstructured documents into pristine structured JSON with 99.8% precision.

Combining deep learning OCR engines (DocTR, LayoutLM) with state-of-the-art Vision LLMs (GPT-4o, Claude 3.5 Sonnet), my pipelines effortlessly parse dense multi-page tables, handwritten notes, and skewed scans.

What I Deliver:

- Custom OCR pipeline built with DocTR, LayoutLM, or OpenCV

- Multimodal Vision LLM extraction with schema constraints

- Complex form parsing (CMS-1500, UB-04, ACORD, invoices & receipts)

- Pydantic schema validation preventing malformed or missing fields

- FastAPI asynchronous REST microservice with Webhook callbacks

- Docker containerization ready for AWS, GCP, Azure, or private VPS

Tech Stack:

Python, DocTR, PyTorch, OpenCV, GPT-4o, Claude 3.5 Sonnet, Pydantic, FastAPI, Docker.

Contact me before ordering with a sample document so I can benchmark accuracy for your specific use case!

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Muhammad T.

Data Scientist and AI Engineer

  • DaFrancia
  • Membro daset 2026
  • Tempo di risposta medio1 ora
  • Lingue

    Inglese, Francese
I am a Data Scientist and AI Engineer with proven experience delivering LLM and ML-powered features into production. I specialize in building end-to-end information extraction workflows, RAG systems, and multi-agent AI architectures. I have a strong track record of driving technical decisions and collaborating with stakeholders to translate requirements into applied AI solutions.

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