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codeananda/README.md

🤖 Adam Murphy | LLM Engineer | LangChain, LangGraph

I transform complex document processing challenges into scalable AI solutions. My systems have:

  • Processed 12M+ documents in 48 hours
  • Slashed mortgage approval times by 52%
  • Cut LLM costs by 75% while increasing accuracy

🚀 Recent Impact Projects

  • Enterprise-scale payslip data extraction with dual-LLM verification - link
  • UK Local Plan analysis pipeline processing 700+ plans weekly - link
  • Massive-scale document embedding system powering LandGPT - link
  • View detailed case studies in pinned repositories

💡 Technical Philosophy

Most of my recent work lives in private repositories (NDAs, enterprise clients). What you see here are carefully documented case studies that showcase my approach to building robust, scalable LLM systems.

🎯 Certifications & Expertise

  • AWS Machine Learning Specialty: Advanced certification in production ML systems and large-scale deployments (achieved December 2024)

🛠 Core Tech Stack

  • LLM Orchestration: LangChain, LangSmith, LangGraph, CrewAI
  • Models: OpenAI, Google Gemini (Studio and Vertex), Anthropic Claude, Groq
  • Infrastructure: AWS, S3, EC2, ECR, AWS Lambda, AWS Fargate, PostgreSQL, Docker, FastAPI
  • Monitoring: Custom observability pipelines, LangSmith dashboards
  • Machine Learning: Pandas, NumPy, Scikit-Learn, XGBoost, PyTorch

🤝 Let's Build Something

Need an LLM system that actually delivers ROI? Check my Upwork profile for availability.

Pinned Loading

  1. enterprise_payslip_data_extractor enterprise_payslip_data_extractor Public

    📈 Enterprise-scale document processing system that slashed mortgage approval times by 52% through dual-LLM verification and CrewAI orchestration.

  2. local_plan_policy_summariser local_plan_policy_summariser Public

    🚀 Automated analysis pipeline processing 700+ UK Local Plans weekly, leveraging Gemini's 2M token context to transform 1000-page PDFs into instant insights while cutting LLM costs by 75%.

  3. planning_doc_text_extract_embed planning_doc_text_extract_embed Public

    📑 Scaled document processing pipeline that chomped through 12 million planning documents in 48 hours using open-source embeddings and Kubernetes spot instances, powering LandGPT's precise citations.

  4. testimonials testimonials Public

    ⭐ A collection of testimonials & LinkedIn recommendations I've received from happy clients over the last 6+ years as a freelance ML/LLM Engineer

    1