Phoenix - Your AI AssistantBuild a RAG application to query your documents and data
Delivery in
3 days
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What you get with this Offer
Chat with Your Data — Production-Ready RAG Applications
I build Retrieval-Augmented Generation (RAG) systems that let you ask natural-language questions of your documents, databases, and knowledge bases—no more manual searching.
What I deliver
- Document Q&A (PDF, Word, CSV, URLs)
- Internal knowledge‑base chatbots
- Customer support bots trained on your content
- Multi‑document search and summarisation
- Custom RAG pipelines with tailored chunking & retrieval strategies
Technology I use
LangChain, LlamaIndex, OpenAI / Anthropic / open-source LLMs, and vector DBs such as Pinecone, Chroma, and Weaviate. I build Python backends with REST or chat interfaces for easy integration.
What you get
- A fully working, production‑ready RAG application
- Clean, well‑documented Python code you own outright
- Setup & configuration documentation
- One round of revisions included
Next step
Message me with your data type and use case (PDFs, databases, URLs, etc.) before ordering and I’ll propose a focused plan.
I build Retrieval-Augmented Generation (RAG) systems that let you ask natural-language questions of your documents, databases, and knowledge bases—no more manual searching.
What I deliver
- Document Q&A (PDF, Word, CSV, URLs)
- Internal knowledge‑base chatbots
- Customer support bots trained on your content
- Multi‑document search and summarisation
- Custom RAG pipelines with tailored chunking & retrieval strategies
Technology I use
LangChain, LlamaIndex, OpenAI / Anthropic / open-source LLMs, and vector DBs such as Pinecone, Chroma, and Weaviate. I build Python backends with REST or chat interfaces for easy integration.
What you get
- A fully working, production‑ready RAG application
- Clean, well‑documented Python code you own outright
- Setup & configuration documentation
- One round of revisions included
Next step
Message me with your data type and use case (PDFs, databases, URLs, etc.) before ordering and I’ll propose a focused plan.
What the Freelancer needs to start the work
Data source — PDFs, Word docs, URLs, database, CSV?
Use case — internal search, customer support, Q&A?
LLM preference — OpenAI, Anthropic, open-source, or no preference?
Interface — chat UI, API only, or embedded widget?
Volume — how many documents and approximate total size?
Hosting — local, cloud, or existing infrastructure?