You will get a custom AI agent with RAG that answers and acts on your data
Project details
Stop paying people to answer the same questions and copy data between tools. I build production AI agents that read your documents and data, answer accurately with source citations (RAG), and take real actions — booking, updating your CRM, creating tickets, and calling your APIs. Built on LangChain/LangGraph with vector search (Pinecone, pgvector) and OpenAI or Anthropic models, deployed as a web widget, API, or Slack/WhatsApp bot. This is an autonomous agent, not a scripted FAQ bot: it retrieves, reasons, uses tools, and knows when to hand off to a human. I've shipped live agentic systems for US and UK clients, including a multimodal support copilot on Pinecone with web-search fallback. As an AI engineer I own the whole build — retrieval, agent logic, integrations, evaluation, and deployment with monitoring. Not sure which tier fits? Send me your use case and I'll recommend one — I reply within 24 hours.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Azure OpenAI, Hugging FaceAI Models
ChatGPT, GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$199
|
Standard
$549
|
Advanced
$1,099
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 25 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | ||
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | ||
Model Documentation | |||
Model Monitoring | - | - | |
Model Testing & Optimization | - | ||
Model Tuning | - | - | - |
Natural Language Processing | |||
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | - | - | - |
Source Code |
Frequently asked questions
About Ahmed
AI Engineer | LLM Apps, Voice Agents and Automation | LangGraph, n8n
Kohat, Pakistan - 8:52 am local time
I'm an AI Engineer who has designed, built, and deployed live AI products for US and UK clients. A few I've shipped:
1. AI Voice-Agent CRM (US e-commerce): Retell AI agents that call customers for cart recovery and win-backs, look up their live Shopify cart mid-call, and text discount codes via Twilio plus a nightly Claude loop that retrains the agents from their own call transcripts.
2. Multimodal RAG Support Copilot (live SaaS): a LangGraph agent that answers technicians' troubleshooting questions from a Pinecone manual index, falls back to live web search, diagnoses from photos, and runs on Stripe billing with per-user token budgets.
3. AI Social-Content Engine (UK brand): LangGraph content generation grounded in a RAG brand knowledge base, routed through a human-in-the-loop approval queue and auto-published on a schedule.
4. AI Health Receptionist Voice Agent: an ElevenLabs voice agent that autonomously books, cancels, and reschedules appointments integrated with the clinic's calendar and taking payment within the same call.
What I can build for you:
1. AI voice agents (Retell AI, ElevenLabs) for support, sales, and appointment booking
2. RAG chatbots and assistants over your documents and data (LangChain, LangGraph, Pinecone, pgvector)
3. Autonomous AI agents and tool-calling workflows
4. Workflow automation (n8n, APIs, Shopify, Gmail, Twilio, Stripe)
5. Full-stack AI products (FastAPI + Next.js + Supabase/Postgres), deployed with Docker and CI/CD
Tech I work with:
- Languages: Python, JavaScript, TypeScript
- LLM and agents: LangChain, LangGraph, CrewAI, RAG, vector search, tool calling
- LLM providers: OpenAI, Anthropic (Claude), Mistral, Groq, Qwen, Hugging Face
- Voice and speech: Retell AI, ElevenLabs, Whisper
- Backend and data: FastAPI, Next.js/React, Supabase, PostgreSQL, Redis, Pinecone
- Automation and deployment: n8n, Docker, CI/CD, Stripe, Twilio, Shopify
I own the whole thing model, backend, integrations, and deployment. So you get a working product, not a prototype.
If you're building an AI voice agent, a RAG chatbot, or an automation that needs to run reliably in production, send me your brief. I reply within 24 hours.
Steps for completing your project
After purchasing the project, send requirements so Ahmed can start the project.
Delivery time starts when Ahmed receives requirements from you.
Ahmed works on your project following the steps below.
Revisions may occur after the delivery date.
Scope, data & tool mapping
We define the agent's tasks, the knowledge sources to index, and the tools/APIs it must call, then I design the retrieval and agent architecture.
Build the agent & integrations
I ingest and index your data, build the RAG pipeline and tool-calling agent, connect your APIs/CRM/database, and add guardrails and human-handoff.