You will get custom GPT chatbot trained on your business documents
Project details
Turn your PDFs, website, knowledge base, or internal docs into a smart AI assistant that answers customer or staff questions accurately using OpenAI Assistants API or RAG with vector search.
What you get:
✓ Document ingestion + chunking pipeline (PDFs, websites, Notion, Sheets)
✓ Vector embedding setup (Pinecone or Supabase pgvector)
✓ Custom system prompt tuned to your business voice
✓ Working chat interface (web widget or API endpoint)
✓ Source citation in every answer (no hallucinations on your watch)
✓ Handover docs + 7 days post-delivery support
Real example: I built HEART-Eco's "Ask AI" panel, clients query a complex economic model in natural language and get cited, model-grounded answers. Live at heart-eco.vercel.app.
What you get:
✓ Document ingestion + chunking pipeline (PDFs, websites, Notion, Sheets)
✓ Vector embedding setup (Pinecone or Supabase pgvector)
✓ Custom system prompt tuned to your business voice
✓ Working chat interface (web widget or API endpoint)
✓ Source citation in every answer (no hallucinations on your watch)
✓ Handover docs + 7 days post-delivery support
Real example: I built HEART-Eco's "Ask AI" panel, clients query a complex economic model in natural language and get cited, model-grounded answers. Live at heart-eco.vercel.app.
AI Algorithms
Convolutional Neural Network, Generative Adversarial Network, Large Language Model, Multilayer Perceptron, Multimodal Large Language Model, Regression AnalysisAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI Text-to-Image, AI Text-to-Speech, AI-Generated Code, AIOps, Automatic Speech Recognition, Conversational AI, Facial Recognition, Image Recognition, Sentiment AnalysisAI Development Language
PythonAI Tools
Bing AI, GitHub Copilot, Hugging Face, Microsoft 365 Copilot, PyTorch, Replit, Streamlit, TensorFlow, Word2vecAI Models
ChatGPT, DALL-E, GPT-3, GPT-4, LLaMA, OpenAI CodexWhat's included $250
These options are included with the project scope.
$250
- Delivery Time 10 days
- Number of Revisions 2
- AI Model Integration
- Model Tuning
- Prompt Engineering
About Mohammad Taiyab
AI Developer | RAG, OpenAI Assistants, Stripe Connect, Next.js
Egham, United Kingdom - 7:58 am local time
What I build for clients:
→ Custom GPT assistants trained on your business documents - RAG over PDFs, websites, knowledge bases (Pinecone / vector DBs)
→ OpenAI Assistants API integrations - natural-language "Ask AI" panels for dashboards, support, and internal tools
→ AI workflow automation with n8n and Make - connect GPT-4 to your existing stack (Sheets, Notion, Slack, Stripe, etc.)
→ Full-stack AI MVPs - Next.js + Node + Python FastAPI + Postgres/Supabase, deployed to Vercel/Railway
→ Stripe Connect and Sharetribe marketplace customizations
Recent shipped work:
• HEART-Eco - Next.js 14 economic forecasting dashboard with multi-pillar scoring + OpenAI Assistants "Ask AI" panel
• Clock-in Pro - Face-verified, GPS-geofenced attendance platform. Scaled to 45 staff across 3 sites, 99.6% uptime, cut payroll errors 72%.
• MummyHelp - Voice-activated SOS app with on-device wake-word detection (Picovoice Porcupine) and speaker verification (SpeechBrain ECAPA-TDNN). 96.8% accuracy.
• Sartorial London - Sharetribe Flex marketplace with custom Stripe security-deposit flow and 5-day rental booking logic.
Why work with me:
Real shipped products with paying clients - not tutorials or sandbox demos.
I document everything: change logs, technical specs, handover docs. You're not stuck if you hire someone else later.
UK-based, fluent English, working in your business hours.
I bring full-stack thinking to AI projects - your prototype actually ships to production.
Happy to do a 15-minute scoping call before we agree anything. Send me a message with what you're trying to build.
Steps for completing your project
After purchasing the project, send requirements so Mohammad Taiyab can start the project.
Delivery time starts when Mohammad Taiyab receives requirements from you.
Mohammad Taiyab works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery & Scoping
We start with a short message exchange (or call if needed) where I understand your data sources, use case, and what questions the AI needs to answer.
Data Ingestion & Embedding
I ingest your documents, website content, or knowledge base clean the text, chunk it correctly, and embed it into a vector store (Pinecone or Supabase pgvector). This is the foundation. If this step is weak, the AI hallucinates. I do it properly.