I will build an offline ai desktop application

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avishekshar
A
avishekshar
Avishek Sharma
Alcune informazioni sono riportate in lingua inglese.

Informazioni su questo servizio

Private Local LLM Chat Apps and RAG Engines


Want the power of Large Language Models without sending data to third-party APIs? I build secure, high-performance, completely offline AI applications tailored to your needs. Run open-source models locally with zero monthly token fees and absolute data privacy.


What I Build:

  1. Local Chat Clients: Ultra-lightweight desktop or web interfaces running models like Llama 3 or Gemma4 or ultra fast liquidAI models.
  2. Air-Gapped RAG Solutions: Complete offline capabilities for sensitive corporate or personal data powered by AI models.


Tech Stack:

  1. Backend: High-throughput Python Fastapi or Rust built for low latency systems.
  2. Inference: Ollama, Llama.cpp, and Hugging Face.
  3. Databases: Local storage and vector databases like SQLite, SurrealDB.
  4. UI: Clean Vue JS responsive interfaces, with modern UI/UX with multi-chat session management.


Why Local AI?

  1. Zero API Bills: Pay once for development, run forever for free.
  2. 100% Privacy: Data never leaves your machine.
  3. Performance: Highly optimized back-ends for fast token streaming.


Please message me before ordering to discuss your hardware setup and project scope!

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Avishek Sharma

High Performance AI Systems Engineer

  • DaIndia
  • Membro dalug 2026
  • Lingue

    Inglese, Hindi
I am a backend systems engineer with over five years of experience architecting high-performance, privacy-first AI applications. My focus is on building robust, air-gapped AI solutions that allow businesses to leverage advanced language models entirely locally, ensuring zero data leakage. I specialize in ultra-efficient local clients and enterprise-grade knowledge assistants. From engineering highly optimized, concurrent back-end pipelines to crafting clean, modern user interfaces, I deliver end-to-end software that operates securely on your own hardware without recurring API costs.

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