Get a production-ready AI agent powered by LangChain, LangGraph, and your choice of OpenAI or a local open-source LLM — complete with source code, documentation, and a working frontend.
I Will Build Custom AI Agents and RAG Applications
A working AI agent integrated with your chosen LLM, with authentication and source code — the essential foundation.
- AI LLM model integration (OpenAI API or local LLM such as LLaMA 3 / Mistral)
- User authentication included
- FastAPI backend setup
- Frontend in React.js / Tailwind or Streamlit
- Full source code handed over
- Setup documentation included
Everything in Starter plus a Retrieval-Augmented Generation pipeline so your agent reasons over your own documents and data.
- All Starter tier features included
- Retrieval-Augmented Generation (RAG) pipeline built on your documents or knowledge base
- Vector store integration for accurate, real-time responses
- FastAPI backend with RAG endpoints
- 2 rounds of revisions
- Full source code and documentation
The complete solution: RAG, CRM or database integration, and a pre-set conversational journey for guided, business-ready interactions.
- All RAG Agent tier features included
- CRM or database integration for live data access
- Pre-set conversational journey for structured user interactions
- Multi-agent or advanced LangGraph workflow where applicable
- 3 rounds of revisions
- Full source code, deployment guidance, and documentation
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Key details about this service to help you decide. Generated by Zinn Hub, not the seller.
Value Position
AI Framework Stack
LLM Flexibility
RAG Availability
Frontend Support
What You'll Receive
Full Description
If your business needs an intelligent AI agent that actually works — one that answers questions, retrieves information from your own data, automates workflows, or handles customer conversations — this is the service for you.
Built by a full-stack AI engineer based in London, every solution is custom-developed using LangChain, LangGraph, LangSmith, and FastAPI. Whether you want to use the OpenAI API or keep everything private with a local open-source model such as LLaMA 3 or Mistral, your agent is configured to your exact requirements.
**What you receive:**
Every engagement includes a fully working AI agent integrated with your chosen LLM, user authentication, complete source code, and setup documentation. Depending on the package you select, your delivery can also include a Retrieval-Augmented Generation (RAG) pipeline trained on your own documents, a pre-set conversational journey for guided interactions, and full CRM or database integration.
Frontend delivery is available in React.js with Tailwind CSS or as a Streamlit interface — whichever suits your team's stack. The backend is served via a FastAPI application, deployable to your own server or cloud platform.
**How the process works:**
After placing your order, simply share your requirements, your preferred LLM (OpenAI or local), and any data or documents the agent should work with. Clear, direct communication happens through the order chat. You will receive regular updates, and revisions are included at every tier. If anything needs clarifying before work begins, you will be contacted promptly.
**Who this is for:**
This service is ideal for startups and established businesses that want AI-powered customer support, internal knowledge base agents, or intelligent automation — without having to manage the complexity of AI infrastructure themselves. It suits technical founders who want clean, handover-ready source code, as well as non-technical teams who simply need a working solution with documentation they can follow.
**Why work with this seller:**
Zinn Digital is a London-based AI engineering practice specialising end-to-end in generative AI, custom chatbots, RAG systems, and multi-agent LangGraph workflows. Every project is delivered with full source code — you own what you pay for. Solutions are built to integrate with real business systems, not just demonstrate a proof of concept.
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Compare Packages
| Feature | Starter AI Agent | RAG Agent | Full AI System |
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 21 days |
| Revisions | 1 | 2 | 3 |
| AI LLM model integration (OpenAI API or local LLM such as LLaMA 3 / Mistral) | ✓ | ✕ | ✕ |
| User authentication included | ✓ | ✕ | ✕ |
| FastAPI backend setup | ✓ | ✕ | ✕ |
| Frontend in React.js / Tailwind or Streamlit | ✓ | ✕ | ✕ |
| Full source code handed over | ✓ | ✕ | ✕ |
| Setup documentation included | ✓ | ✕ | ✕ |
| All Starter tier features included | ✕ | ✓ | ✕ |
| Retrieval-Augmented Generation (RAG) pipeline built on your documents or knowledge base | ✕ | ✓ | ✕ |
| Vector store integration for accurate, real-time responses | ✕ | ✓ | ✕ |
| FastAPI backend with RAG endpoints | ✕ | ✓ | ✕ |
| 2 rounds of revisions | ✕ | ✓ | ✕ |
| Full source code and documentation | ✕ | ✓ | ✕ |
| All RAG Agent tier features included | ✕ | ✕ | ✓ |
| CRM or database integration for live data access | ✕ | ✕ | ✓ |
| Pre-set conversational journey for structured user interactions | ✕ | ✕ | ✓ |
| Multi-agent or advanced LangGraph workflow where applicable | ✕ | ✕ | ✓ |
| 3 rounds of revisions | ✕ | ✕ | ✓ |
| Full source code, deployment guidance, and documentation | ✕ | ✕ | ✓ |
Portfolio
Examples of the seller's work related to this Zinn.
Build Custom AI Agents and RAG Applications
Build Custom AI Agents and RAG Applications
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Frequently Asked Questions
An AI Agent is an intelligent program that can answer questions, retrieve information, automate repetitive workflows, or handle customer conversations — all driven by an AI language model. It can be powered by the OpenAI API (cloud-based) or a local open-source model such as LLaMA 3 or Mistral for full data privacy.
The OpenAI API is cloud-hosted, fast, and requires an API key — your data is processed on OpenAI's servers. A local LLM (such as LLaMA 3, Mistral, or Vicuna) runs on your own machine or private server, meaning no data leaves your environment and there are no ongoing API costs. The right choice depends on your privacy requirements and infrastructure.
RAG (Retrieval-Augmented Generation) combines a vector-based search over your own documents with a generative AI model. Instead of the AI guessing or hallucinating, it retrieves accurate information directly from your knowledge base before generating a response. This is essential for customer support agents, internal FAQs, and any scenario where accuracy matters.
After placing your order, please share: your project requirements and goals, your preferred LLM (OpenAI API key or local model preference), any documents or data the agent should work with (for RAG projects), and your preferred frontend (React.js or Streamlit). If anything is unclear, you will be contacted via the order chat before work begins.
Yes. The backend is built with FastAPI and can be deployed to your own server or cloud platform, making the agent accessible via a web application or API endpoint. The Full AI System tier includes deployment guidance as standard.
Yes — full source code is included in every tier. You receive complete ownership of all code produced, along with setup documentation so your team can maintain, extend, or modify it independently.
Revisions are included as stated in each package (1 for Starter, 2 for RAG Agent, 3 for Full AI System). A revision covers adjustments to the delivered work based on your original brief. Significant scope changes beyond the agreed requirements would be treated as a new request and discussed via the order chat.
Frontends can be built in React.js with Tailwind CSS, plain HTML/CSS/JavaScript, or Streamlit — depending on your preference and the complexity of the interface required. This is confirmed during the initial requirements discussion.
Customer Reviews
See what our customers say about this Zinn
An excellent professional, he assisted me on several more projects.
It was truly a pleasure working with Syed. He not only understood my requirements clearly but also delivered the project on time with exceptional quality. Throughout the process, he was patient, attentive, and receptive to every change I requested. His communication was excellent, and he consistently ensured I was satisfied at every stage of the work. Syed demonstrated professionalism, strong work ethic, attention to detail, and great problem-solving ability. I was impressed by his dedication and commitment to delivering outstanding results. I would highly recommend Syed to anyone looking to hire a reliable and skilled professional.
Syed did an outstanding job for a RAG. He was extremely attentive, precise, and always made sure to fully understand the requirements before moving forward. Communication was smooth and professional throughout the entire project. Highly recommended — I’d definitely work with him again!
Zain delivered an exceptional MVP for the CareAs AI platform. He completed all Milestones 1 to 4 exactly to the acceptance criteria and even fixed items I had missed. He built a strong FastAPI backend, a reliable RAG care-plan engine with citations, clinical rule checks, and a clean React UI with 22 pages. Azure deployment was smooth with CI/CD, Blob Storage, secure configs and model switching. Communication was clear, he demoed often, resolved issues quickly, and understood UK care home and CQC needs. Professional, skilled, and I am happy to work with him again on future features.
I love working with him.
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