You will get working AI MVP with RAG, AI agents and business automation
Rising Talent
Rising Talent
Project details
Turn your AI idea into a functional MVP ready for real user testing.
I will design and build one focused AI product using RAG, AI agents, workflow automation, or a combination of these technologies. Your MVP can be a customer support assistant, internal knowledge tool, sales agent, ecommerce assistant, document analysis system, lead qualification workflow, or an AI feature for an existing platform.
The project may include an AI chat interface, business-data retrieval, vector database, prompt engineering, one external integration, backend API, testing, deployment, source code, and documentation.
I work with OpenAI, Claude, Gemini, LangChain, LangGraph, Python, FastAPI, vector databases, n8n, APIs, and modern web frameworks.
I have built agentic ecommerce assistants for established UK businesses operating at approximately £2.5M in annual revenue. My focus is not a generic chatbot, but a practical AI workflow that solves a real business problem and can be tested with customers, employees, or investors.
Please contact me before ordering if your project requires multiple agents, complex integrations, or a full SaaS platform.
I will design and build one focused AI product using RAG, AI agents, workflow automation, or a combination of these technologies. Your MVP can be a customer support assistant, internal knowledge tool, sales agent, ecommerce assistant, document analysis system, lead qualification workflow, or an AI feature for an existing platform.
The project may include an AI chat interface, business-data retrieval, vector database, prompt engineering, one external integration, backend API, testing, deployment, source code, and documentation.
I work with OpenAI, Claude, Gemini, LangChain, LangGraph, Python, FastAPI, vector databases, n8n, APIs, and modern web frameworks.
I have built agentic ecommerce assistants for established UK businesses operating at approximately £2.5M in annual revenue. My focus is not a generic chatbot, but a practical AI workflow that solves a real business problem and can be tested with customers, employees, or investors.
Please contact me before ordering if your project requires multiple agents, complex integrations, or a full SaaS platform.
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System, Software MaintenanceAI Tools
deeplearn.js, Google AutoML, Keras, MLflow, PyTorch, TensorFlowAI Development Language
PythonWhat's included $749.99
These options are included with the project scope.
$749.99
- Delivery Time 12 days
- Number of Revisions 2
About Usman Shoukat
AI Chatbot & Agent Developer | RAG, Python, FastAPI | n8n, LangChain
Romford, United Kingdom - 8:02 am local time
I build AI chatbots, RAG systems and automations in Python that are tested before they go live. Most recently: a production AI shopping assistant and staff dashboard running inside a business doing $2.5M+ a year.
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WHAT I BUILD
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AI chatbots that answer from your real data
Live catalogue, order status, policies, internal docs. Vector search over your own Postgres, so the bot quotes what you actually published instead of improvising. When it doesn't know, it says so and hands off to a person.
RAG over your documents
Upload contracts, manuals, help centre articles or specs and get answers with the source attached. Built on PostgreSQL and pgvector — no extra vendor, no per-query pricing, your data stays in your own database.
Staff dashboards for the AI you already run
Watch conversations live, take over mid-chat, replay any past conversation exactly as the customer saw it, and see which leads browsed but never bought. React and TypeScript on a FastAPI backend.
n8n automation and API integration
Connecting Gmail, Slack, Sheets, CRMs, Stripe and any REST API or webhook — including fixing the broken build you inherited from someone else.
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WHY MINE DOESN'T MAKE THINGS UP
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Two things most builds skip:
Every generated reply is scanned before it reaches your customer. If it contains a price, dimension or feature claim that isn't in the data actually retrieved for that question, it doesn't get sent. Grounding is enforced in code, not requested in a prompt.
I don't hand the model a set of tools and hope it picks correctly. The question is classified once, then plain Python functions run deterministically — database lookup, order fetch, price math. It is cheaper, faster and it cannot wander off mid-conversation. Reliability comes from constraining the model, not giving it more freedom.
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IT KEEPS WORKING AFTER I LEAVE
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Before launch I build a test corpus from your real conversations and snapshot how the bot handles each one. Every prompt change, model change or new data source re-runs it and flags any question that now gets routed somewhere different. A "small tweak" cannot quietly start sending customers to the wrong answer without someone seeing it. Handover includes the harness, a written doc and a Loom walkthrough, plus 14 days of free fixes.
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BUILT WITH
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Python · FastAPI · PostgreSQL · pgvector · Supabase · OpenAI API · n8n · TypeScript · React · Shopify API · REST APIs · Webhooks
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HOW IT STARTS
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Send me 20 real examples of the questions or the work you want handled. No technical vocabulary needed. I'll tell you what AI should and shouldn't touch — some of it is cheaper and more reliable as plain code, and I'll say so. Then a small paid pilot you can judge before committing to anything bigger.
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Tell me the process eating your team's week. You'll get a plain-English answer on whether it can be automated, what it takes and roughly what it costs — before you hire anyone.
Steps for completing your project
After purchasing the project, send requirements so Usman Shoukat can start the project.
Delivery time starts when Usman Shoukat receives requirements from you.
Usman Shoukat works on your project following the steps below.
Revisions may occur after the delivery date.
Approval
I accept the project. before starting the project.