You will get custom AI knowledge assistant trained on your data
Top Rated
Project details
If you're a consulting business, you likely have tons of docs, instructions, and support tickets across Trello, SharePoint, Google Drive, Asana, Zendesk etc. Finding what you need takes time and eats hours of your team’s day.
I build production-ready RAG systems that let your team or customers ask questions directly from your documents, knowledge base, or website, with accurate, source-grounded responses.
What you get:
• Document ingestion (PDFs, website, internal docs)
• Vector database + semantic search setup
• LLM integration (OpenAI / Claude)
• Retrieval pipeline for accurate answers
• Chat interface or API
• Deployment Plan & documentation
This solution works well for:
• AI customer support assistants
• internal knowledge copilots
• document search tools
• SaaS products adding AI features
You’ll get a working RAG system trained on your data, ready to integrate into your product or internal workflows.
It can be delivered as a chat interface or integrated into your existing product through an API.
If you're exploring how to add AI to your product or internal workflows, feel free to reach out and we can discuss the best way to simplify your operations.
I build production-ready RAG systems that let your team or customers ask questions directly from your documents, knowledge base, or website, with accurate, source-grounded responses.
What you get:
• Document ingestion (PDFs, website, internal docs)
• Vector database + semantic search setup
• LLM integration (OpenAI / Claude)
• Retrieval pipeline for accurate answers
• Chat interface or API
• Deployment Plan & documentation
This solution works well for:
• AI customer support assistants
• internal knowledge copilots
• document search tools
• SaaS products adding AI features
You’ll get a working RAG system trained on your data, ready to integrate into your product or internal workflows.
It can be delivered as a chat interface or integrated into your existing product through an API.
If you're exploring how to add AI to your product or internal workflows, feel free to reach out and we can discuss the best way to simplify your operations.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI-Enhanced Classification, Natural Language Generation, Sentiment AnalysisAI Development Language
PythonAI Tools
Azure OpenAI, Hugging FaceAI Models
GPT-4, LLaMA, WhisperWhat's included
| Service Tiers |
Starter
$4,000
|
Standard
$7,000
|
Advanced
$10,000
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 15 days |
Number of Revisions | 1 | 3 | 5 |
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 | - | - | - |
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DW
Dan W.
Apr 16, 2026
Build Azure-Hosted Python Web App for “Chat with Employee Handbook” (RAG / Azure OpenAI)
I had an excellent experience working with Hamza on this project. Communication and responsiveness, quality of work, timeliness, five stars all around. Would definitely work with him again.
AL
Armando L.
Sep 2, 2025
Developer Needed for Rule-Based AI Day Trading App
GREAT TEAM! Hamza and his team did a great job! My Project is working great and I will totally work with him again in future projects.
ME
Maran E.
Aug 16, 2025
Email Marketing Automation: Integrate Memberstack Data with Klaviyo
AS
Amanda S.
Jul 17, 2025
Technical Project Manager | Agile & Software Development
Hamza was an excellent resource who helped complete my project quickly and effectively. I would highly recommend Hamza!
AB
Alan B.
Jul 15, 2025
Automated Newsletter System
I appreciate your help. We will work again thank you.!
About Hamza
Senior AI Engineer | LLM, Automation, RAG & AI Agents | 10+ years
100%
Job Success
Toronto, Canada - 12:08 pm local time
𝐌𝐨𝐬𝐭 𝐟𝐫𝐞𝐞𝐥𝐚𝐧𝐜𝐞𝐫𝐬 𝐛𝐮𝐢𝐥𝐝 𝐩𝐫𝐨𝐭𝐨𝐭𝐲𝐩𝐞𝐬. 𝐈 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭, 𝐬𝐡𝐢𝐩 𝐚𝐧𝐝 𝐬𝐭𝐚𝐧𝐝 𝐛𝐞𝐡𝐢𝐧𝐝 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐬𝐲𝐬𝐭𝐞𝐦s
𝐖𝐡𝐚𝐭 𝐌𝐚𝐤𝐞𝐬 𝐌𝐞 𝐃𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭:
▸ I own outcomes, not tasks: I become your technical partner who flags risks early, communicates proactively and takes end-to-end responsibility.
▸ Masters in Data Science + 10 yrs engineering: I bring rigorous thinking on architecture, model selection and RAG design, not just prompt engineering.
▸ I say no to bad fits: When I say yes, I'm fully committed. I don't take on work I can't do exceptionally well.
𝐄𝐧𝐝-𝐭𝐨-𝐄𝐧𝐝 𝐀𝐈 𝐚𝐧𝐝 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭
▸ 𝐋𝐋𝐌 𝐏𝐨𝐰𝐞𝐫𝐞𝐝 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬
RAG pipelines, AI agents, multi-agent systems, agent orchestration, AI copilots, document intelligence, custom chatbots
▸ 𝐀𝐈 & 𝐃𝐚𝐭𝐚 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬
Predictive scoring engines, business intelligence dashboards, embeddings, vector search and data pipelines your team actually relies on.
▸ 𝐑𝐞𝐯𝐞𝐧𝐮𝐞 𝐎𝐩𝐬 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧
Sales, marketing & internal ops automation via n8n, Make, Zapier. CRM integrations: HubSpot, GoHighLevel, Pipedrive, ActiveCampaign, Zoho.
▸ 𝐕𝐨𝐢𝐜𝐞 𝐀𝐈 & 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐒𝐲𝐬𝐭𝐞𝐦𝐬
Inbound and outbound AI calling systems built on Vapi, Twilio and Voiceflow for lead qualification, scheduling, and support.
▸ 𝐁𝐚𝐜𝐤𝐞𝐧𝐝 & 𝐅𝐮𝐥𝐥-𝐒𝐭𝐚𝐜𝐤 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠
Python (FastAPI, Django, Flask), Node.js, Go. Frontend: React, Next.js, Tailwind. Cloud: AWS, GCP, Azure, Docker, Kubernetes, CI/CD.
𝐇𝐨𝐰 𝐈 𝐖𝐨𝐫𝐤:
▸ Scoping (Free): We align on problem, users, and success criteria. I'll tell you honestly if I'm the right fit.
▸ Architecture & Plan: Technical plan with milestones before writing a line of code. No surprises.
▸ Build & Ship: Focused sprints, weekly updates, working software not status decks.
▸ Launch & Support: I don't disappear. 30-day support included, retainers available.
𝐑𝐞𝐜𝐞𝐧𝐭 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
▸ Sortsy, LLM-powered file organiser, production-shipped in under 3 months, 650+ paying customers
▸ Predictive Real Estate Intelligence Platform with automated data pipelines
▸ AI based Royalty Attribution System for music industry enterprise client
𝐓𝐄𝐂𝐇 𝐒𝐓𝐀𝐂𝐊
𝐀𝐈/𝐋𝐋𝐌𝐬: GPT-4o, Claude, Gemini, OpenAI API, Anthropic API, Azure OpenAI, OpenClaw, Llama, Mistral, HuggingFace, Whisper | 𝐎𝐫𝐜𝐡𝐞𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧: LangGraph, LlamaIndex, LangChain, CrewAI, AutoGen, Pydantic AI, tool calling, function calling, agent orchestration, multi-agent workflows, memory, session memory
𝐑𝐀𝐆 & 𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐚𝐥: Hybrid Search (BM25 + vector), semantic search, GraphRAG, agentic RAG, re-ranking (Cohere), chunking, metadata filtering, grounding, hallucination reduction, retrieval systems, knowledge assistants, document intelligence, pgvector, FAISS, Redis Vector, Pinecone, Qdrant, Weaviate, ChromaDB, Elasticsearch | 𝐄𝐯𝐚𝐥𝐬 & 𝐎𝐛𝐬𝐞𝐫𝐯𝐚𝐛𝐢𝐥𝐢𝐭𝐲: evaluation, prompt versioning, observability, latency optimization, cost optimization
𝐅𝐢𝐧𝐞-𝐭𝐮𝐧𝐢𝐧𝐠 & 𝐈𝐧𝐟𝐞𝐫𝐞𝐧𝐜𝐞: LoRA/PEFT, vLLM
𝐁𝐚𝐜𝐤𝐞𝐧𝐝: Python, FastAPI, Django, Flask, Node.js, Go, Redis, Celery, Kafka, AI APIs, backend automation, webhook integrations, event-driven workflows | 𝐅𝐫𝐨𝐧𝐭𝐞𝐧𝐝: React, Next.js, Tailwind, v0 |
𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬: PostgreSQL, MongoDB, Supabase, Elasticsearch
𝐂𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬: AWS, GCP, Azure, Docker, Kubernetes, Terraform, CI/CD, production deployment, scalable AI systems | 𝐃𝐞𝐯 𝐓𝐨𝐨𝐥𝐬: Cursor, Claude Code, Codex, LangSmith
𝐕𝐨𝐢𝐜𝐞 & 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐀𝐈: Vapi, Retell AI, Twilio, ElevenLabs, Deepgram, voice agents, AI copilots, conversational AI
𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧: n8n, Make, Zapier, workflow automation, business process automation, API automation, CRM automation, internal operations automation, lead qualification automation, appointment booking automation
𝐂𝐑𝐌𝐬: HubSpot, GoHighLevel, Pipedrive, ActiveCampaign, Zoho, Airtable, Google Workspace
Building an AI system and need it production-ready? Send me a quick overview. I'll respond within a few hours with honest feedback on fit, scope, and approach.
𝐍𝐨 𝐬𝐚𝐥𝐞𝐬 𝐩𝐢𝐭𝐜𝐡. 𝐍𝐨 𝐩𝐫𝐞𝐬𝐬𝐮𝐫𝐞. 𝐉𝐮𝐬𝐭 𝐚 𝐬𝐭𝐫𝐚𝐢𝐠𝐡𝐭 𝐚𝐧𝐬𝐰𝐞𝐫.
Steps for completing your project
After purchasing the project, send requirements so Hamza can start the project.
Delivery time starts when Hamza receives requirements from you.
Hamza works on your project following the steps below.
Revisions may occur after the delivery date.
Review your documents and design the RAG architecture.
Build the ingestion pipeline and vector database.