You will get custom autonomous AI agent built with Python, LangGraph & LLMs
Project details
You will get a custom autonomous AI agent built with Python, LangGraph, and modern LLMs engineered to run in production, not just work in a demo. Most AI agent projects fail the same way: they perform well in testing, then break on real inputs, cost more than expected, or give clients no visibility into what the agent is actually doing. I close that gap.
Every agent I build is designed around three things: reliability (proper error handling, retries, and cost controls so it keeps running), observability (structured logging and tracing so you can see every decision it makes), and scalability (clean architecture so you can add tools, data, or agents later without a rewrite).
Whether you need a single-purpose agent, a multi-agent LangGraph system, or a full workflow automation connected to your existing tools and data, I scope the work clearly upfront and deliver working, documented code not just a prototype that looks good in a call.
Every agent I build is designed around three things: reliability (proper error handling, retries, and cost controls so it keeps running), observability (structured logging and tracing so you can see every decision it makes), and scalability (clean architecture so you can add tools, data, or agents later without a rewrite).
Whether you need a single-purpose agent, a multi-agent LangGraph system, or a full workflow automation connected to your existing tools and data, I scope the work clearly upfront and deliver working, documented code not just a prototype that looks good in a call.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI-Generated Code, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Azure OpenAI, Hugging Face, PyTorch, Streamlit, TensorFlowAI Models
ChatGPT, GPT-4, LLaMA, OpenAI Codex, WhisperWhat's included
| Service Tiers |
Starter
$99
|
Standard
$299
|
Advanced
$699
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 20 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 |
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GS
Gureey S.
May 13, 2026
Need AI Automation Engineer to Scale Our System
I hired Asad to fix a critical call drop issue in my AI calling system. The problem was deep in the Twilio trunk configuration and he diagnosed it quickly, rebuilt everything from scratch and tested it thoroughly. All calls are now completing successfully with no drops. Beyond just fixing the bug, he also helped scale the system for higher volume. He communicated clearly at every step and delivered ahead of schedule. One of the most technically strong developers I've worked with in AI automation. Will definitely hire again for future projects.
About Asad
AI Engineer | Agentic AI, LLM SaaS, Automation & RAG Systems
Lahore, Pakistan - 5:10 pm local time
I am a Senior AI Engineer with of hands-on experience shipping AI that runs reliably in the real world. If you have an idea for an AI agent, chatbot, or LLM feature and you want it built the right way tested, scalable, and ready for real users that's what I do.
WHAT I DO BEST
AGENTIC AI & MULTI-AGENT SYSTEMS
This is my main focus. I build AI agents that plan, make decisions, use
tools, and finish multi-step tasks on their own.
→ Multi-agent systems with LangGraph, LangChain, CrewAI, and AutoGen
→ RAG pipelines with Pinecone, Chroma, Weaviate, and pgvector
→ Agents that connect to your CRM, APIs, and databases
→ Long-term memory and stateful workflows
→ Human-in-the-loop review, monitoring, and safe fallbacks
GENERATIVE AI & LLM APPS
→ Custom LLM apps using GPT-4o, Claude, Gemini, Llama, and Mistral
→ RAG with hybrid search and reranking for accurate answers
→ Document intelligence: clean data from PDFs, Word, and scans
→ LLM evaluation, guardrails, and cost control so agents stay reliable
AI VOICE AGENTS & CHATBOTS
→ Inbound and outbound voice agents (Vapi, Retell, ElevenLabs, Twilio)
→ 24/7 call handling, booking, and smart human handoff
→ Website and WhatsApp chatbots for leads and support
→ Multilingual chat and voice
AI AUTOMATION & INTEGRATION
→ Lead follow-up across Email, SMS, and WhatsApp
→ CRM and pipeline automation (HubSpot, Salesforce, GoHighLevel)
→ AI integrated into your existing web apps, CRMs, and tools via API
→ Tools: n8n, Make, Zapier, and custom API integrations
LLM FINE-TUNING & CUSTOM MODELS
→ Fine-tuning open models (Llama, Mistral) with LoRA and QLoRA
→ Prompt engineering and instruction tuning for better accuracy
→ Custom embeddings and domain-specific model training
→ Evaluation pipelines to measure and improve model quality
COMPUTER VISION & OCR
→ Image classification, object detection, and segmentation
→ OCR and document parsing from PDFs, scans, and photos
→ Custom vision model training and fine-tuning
→ Vision pipelines integrated into your apps and workflows
BACKEND & AI SAAS DEPLOYMENT
Good AI needs a solid backend. I build the infrastructure that keeps it
running at scale.
→ FastAPI, Django, and Flask backends
→ Multi-tenant AI SaaS with authentication and billing
→ Real-time AI streaming with WebSockets
→ PostgreSQL, MongoDB, Redis, and Supabase
→ Docker, AWS, GCP, and CI/CD deployments
TECH STACK
AI: LangGraph, LangChain, CrewAI, AutoGen, OpenAI, Anthropic, Hugging Face, PyTorch
LLMs: GPT-4o, Claude, Gemini, Groq, Mistral, Llama
Vision: OpenCV, YOLO, PyTorch, Tesseract, Roboflow
Backend: Python, FastAPI, Django, Flask
Data: PostgreSQL, MongoDB, Redis, Supabase, Pinecone, Chroma, Weaviate
Cloud: AWS, GCP, Docker, Railway, GitHub Actions
Voice: Vapi, Retell, ElevenLabs, Synthflow, Bland
LET'S TALK
Send me your use case and I'll tell you honestly if it's a good fit, how
I'd build it, and what it takes to get it running in production.
Keywords: AI Engineer, Full-Stack AI Engineer, AI Agent Developer, AI
Automation Engineer, Voice AI Developer, AI Chatbot Developer, Generative
AI, LLM Developer, RAG Developer, LangChain Developer, LangGraph,
Multi-Agent Systems, GPT Developer, OpenAI API, Claude API, AI Integration,
AI SaaS Development, FastAPI Developer, Django Developer, Python Developer,
Prompt Engineering, Fine-Tuning, Computer Vision, n8n Developer, Vapi,
Retell AI, ElevenLabs, Conversational AI, Document AI, OCR
Steps for completing your project
After purchasing the project, send requirements so Asad can start the project.
Delivery time starts when Asad receives requirements from you.
Asad works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements review
I review your requirements and confirm the agent's scope the task, inputs, tools to connect, and the expected output before any work begins.
Architecture & design
I design the agent's structure: how it plans, reasons, uses tools, and manages state, so the build is solid before I write production code.