I will build an offline ai desktop application

A
avishekshar
A
avishekshar
Avishek Sharma

About this gig

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!

Get to know Avishek Sharma

Avishek Sharma

High Performance AI Systems Engineer

  • FromIndia
  • Member sinceJul 2026
  • Languages

    English, 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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