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I will do llm integration lang chain fine tuning software development
ABDULREHMAN
About this gig
I build production-ready AI apps using LangChain, vector databases, and fine tuning. 4+ years full-stack shipped 15+ AI products since 2024.
What I deliver:
Software development end-to-end: backend, API, frontend, deployment. No toy scripts.
LLM integration with OpenAI, Claude, or open-source models. I handle prompts, memory, and API cost optimization.
Vector database setup using Pinecone/Supabase for RAG. Upload PDFs, Notion, docs and chat with your data.
Lang Chain pipelines for agents, tools, and multi-step workflows. Clean, maintainable code.
Fine tuning on your dataset when RAG isnt enough. Consistent tone, domain expertise, lower latency.
Use cases I ship:
AI chatbots, document analyzers, AI SaaS, internal tools, customer support AI, research assistants.
My process:
Discovery call, milestone delivery, Loom updates. You get 100% source code, no vendor lock-in. I optimize for accuracy, speed, and cost.
Your data stays private. If you want AI software development done right with proper LLM integration, vector databases, LangChain, and fine tuning when needed, message me your idea.
Let's Build Your Project!!
Get to know ABDULREHMAN
ABDULREHMAN
Full stack developer
- FromPakistan
- Member sinceApr 2026
- Avg. response time1 hour
Languages
English
Hi, I'm Abdulrehman an experienced Full-stack developer with 4+ years building scalable web and mobile apps. I craft clean, secure code using MERN/MEAN stack, Node.js, React, and Flutter. Delivered 10+ high-traffic websites, 5 CRM/ERP systems, and 7 mobile apps with API-first integrations like Stripe, Firebase, and Twilio. My focus: developer-friendly code that lasts. No cookie-cutter timelines. Let’s connect to map success for your project.
Regards,
Abdulrehman.
My Portfolio
FAQ
What tech stack do you use?
I develop production-ready AI apps: custom chatbots, RAG applications, AI SaaS platforms, document analyzers, AI agents, and internal AI tools. Full-stack with LLM integration using OpenAI, Anthropic, or open-source models via LangChain
How do you handle data security and privacy?
I build with security first: encrypted API calls, no data storage on my end, GDPR-compliant architecture. For sensitive data, I use self-hosted LLMs or on-premises vector databases. Your data never trains public models.
What’s the difference between fine-tuning and RAG?
Fine-tuning teaches the model your specific tone/data, best for consistent outputs. RAG uses vector databases like Pinecone/Supabase to let the AI search your docs in real-time, best for large/updating data. I’ll recommend the right one after reviewing your use case.
