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I will build an ai chatbot or llm app with rag and source citations
CODEAEX
About this gig
Are you looking for an AI chatbot that actually answers from YOUR data not generic responses?
I build production-ready AI and LLM applications that are grounded in your own documents, databases, and knowledge bases. Every answer comes with source citations so your users can verify and trust the response.
We've shipped a production support assistant that answers from company documentation with citations on every response, sub-2-second latency, and automatic escalation when confidence is low.
WHAT YOU GET:
- Custom AI chatbot trained on your documents,
- PDFs, website, or knowledge base RAG (Retrieval-Augmented Generation) with hybrid search for accurate answers
- Source citations on every response no hallucination
- Agent orchestration for multi-step tasks and tool use
- Evaluation pipeline and guardrails to keep responses safe and on-topic
- Clean, modern chat interface built with React / Next.js
- API endpoint so you can integrate with your existing app or website
- Full deployment on your infrastructure (AWS, Vercel, or Docker)
TECH STACK:
Python, LangChain, pgvector, FastAPI, Claude API, OpenAI, Hugging Face, Next.js, PostgreSQL, Docker, AWS
Message me before ordering so we can discuss
Get to know CODEAEX
CODEAEX
AI , Full Stack Developer LLM Apps, SaaS , eCommerce
- FromPakistan
- Member sinceAug 2026
Languages
English
We're Codeaex — an AI and full stack development studio based in Lahore. We build LLM-powered apps, machine learning systems, SaaS platforms, and eCommerce stores. Our shipped projects include a multi-tenant accreditation platform (AMS), a business management system (FMS), marketplace management tools, and hospitality booking sites. Tech stack: Python, TypeScript, React, Next.js, FastAPI, Node.js, PostgreSQL, LangChain, AWS, Docker. Code and cloud stay yours — always.
FAQ
What LLMs do you support?
Claude (Anthropic), GPT-4/GPT-4o (OpenAI), Llama, Mistral, and other open-source models via Hugging Face. I recommend the best model for your use case and budget
Will the chatbot hallucinate?
We build grounding and citation systems specifically to prevent this. Every response is traced back to source documents. When the system is not confident, it escalates to a human rather than guessing.
Do you deploy it too?
Yes. Full deployment on AWS, Vercel, Google Cloud, or Docker. You get the code, the infrastructure, and the deployment pipeline.
Can I add more documents later?
Absolutely. The ingestion pipeline is built for ongoing updates. You can add, remove, or update documents and the system re-indexes automatically.
What about ongoing costs?
I design systems with cost ceilings and caching to minimize API costs. I'll give you a cost estimate before we start based on your expected volume
