You will get Build Custom AI App, RAG System, LLM Backend with FastAPI
Rising Talent
Project details
AI applications, RAG systems, and scalable LLM backends that go beyond basic chatbot implementations. Whether you're building an AI SaaS product, internal AI tool, customer support assistant, or domain-specific copilot, I can help build it properly.
This includes:
• GPT / Claude-powered AI applications
• Retrieval-Augmented Generation (RAG) systems
• AI copilots and conversational assistants
• FastAPI backend architecture
• Vector databases and document pipelines
• Multi-agent workflows and orchestration
• API integrations and automation systems
• AWS/GCP deployment-ready infrastructure
I prioritize:
• Scalable architecture
• Clean backend design
• Low-latency execution
• Reliable orchestration
• Production-ready deployment
If you need an AI system that works reliably beyond the MVP stage, please reach out today
This includes:
• GPT / Claude-powered AI applications
• Retrieval-Augmented Generation (RAG) systems
• AI copilots and conversational assistants
• FastAPI backend architecture
• Vector databases and document pipelines
• Multi-agent workflows and orchestration
• API integrations and automation systems
• AWS/GCP deployment-ready infrastructure
I prioritize:
• Scalable architecture
• Clean backend design
• Low-latency execution
• Reliable orchestration
• Production-ready deployment
If you need an AI system that works reliably beyond the MVP stage, please reach out today
AI Algorithms
Autoencoder, Feedforward Neural Network, Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI Text-to-Speech, AI-Generated Code, AIOps, Automatic Speech Recognition, Conversational AI, Natural Language Generation, Natural Language Understanding, Sequence Modeling, Speech SynthesisAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Gradio, Hugging Face, PyTorch, StreamlitAI Models
BERT, ChatGPT, GPT-4, LLaMA, WhisperWhat's included
| Service Tiers |
Starter
$499
|
Standard
$1,399
|
Advanced
$4,000
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 21 days |
Number of Revisions | 1 | 1 | 2 |
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 |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$1,200 - $5,000
Additional Revision
+$390Frequently asked questions
About Bilal
AI Engineer | AI Agents, RAG, Voice AI & Automation
Birmingham, United Kingdom - 11:36 pm local time
My work goes beyond prompt-level setups into full system design, backend architecture, and deployable AI infrastructure, helping startups and SaaS teams move from basic GPT integrations to stateful, scalable systems with proper orchestration, observability, and failure handling.
What I Deliver ☟
• AI agents with tool execution, workflow routing, and operational automation
• LLM-powered applications (OpenAI, Claude, multi-model systems)
• Claude AI / Anthropic API integration
• RAG systems, AI copilots, and multi-agent workflows to automate decisions and processes.
• End-to-end automation pipelines
• AI voice agents (real-time + async) & STT/TTS pipelines (Whisper, Assembly AI)
• FastAPI-based systems with robust API integrations (Notion, Google, Stripe)
• Production-ready patterns like rate limiting, retries, and queue-based processing
• Docker, CI/CD, and AWS/GCP, with a strong focus on monitoring, logging, and reliability
• Python, Node.js, LangChain, vector databases, and automation frameworks
• Built end-to-end AI platforms from workflow design and orchestration through backend APIs.
My recent work has included AI systems for SaaS, automation, and data-intensive operations, with a focus on scalable architecture, workflow orchestration, and production reliability ☟
• AI Calling Agent with real-time STT/TTS, RAG, escalation logic, and conversation state management
• AI Operations Copilot connecting CRM, APIs, Notion, and internal knowledge into a unified operational workflow
• AI Lead Generation Engine automating prospect discovery, scoring, outreach, and performance tracking
• AI Email Copilot for Outlook with context-aware response generation
• Intelligent Invoicing & SAP HANA Platform automating OCR extraction, approval routing, fraud detection, GL coding, and financial operations workflows
If you're building AI-driven products, automation systems, or scalable LLM applications, I'm open to architecture reviews, MVP builds, and long-term AI systems work.
For larger systems, I usually start with the first workflow milestone so the approach can be validated before expanding the full build.
Let's connect and discuss your use case.
Steps for completing your project
After purchasing the project, send requirements so Bilal can start the project.
Delivery time starts when Bilal receives requirements from you.
Bilal works on your project following the steps below.
Revisions may occur after the delivery date.
AI System Architecture & Development
Design, development, integration, testing, and deployment of the AI application, RAG pipeline, or backend system based on project requirements.