You will get autonomous AI Agents for complex business workflows using LangGraph
Rising Talent
Project details
Stop settling for rigid automations. Move to Agentic Intelligence.
Most "AI Automations" on this platform are simple drag-and-drop workflows that break when things get complex. As a Computer Science specialist and former Teaching Assistant for Programming for AI, I build custom-coded, autonomous systems that actually "think".
Why choose this project?
Advanced Logic: I use LangGraph for cyclic workflows, allowing agents to backtrack and fix their own mistakes.
High Performance: Custom Python code is faster, more secure, and cheaper to run than third-party subscription platforms.
Technical Stack: Python, LangChain, CrewAI, LangGraph, FastAPI, Docker, and Vector Databases (Pinecone/ChromaDB).
Most "AI Automations" on this platform are simple drag-and-drop workflows that break when things get complex. As a Computer Science specialist and former Teaching Assistant for Programming for AI, I build custom-coded, autonomous systems that actually "think".
Why choose this project?
Advanced Logic: I use LangGraph for cyclic workflows, allowing agents to backtrack and fix their own mistakes.
High Performance: Custom Python code is faster, more secure, and cheaper to run than third-party subscription platforms.
Technical Stack: Python, LangChain, CrewAI, LangGraph, FastAPI, Docker, and Vector Databases (Pinecone/ChromaDB).
AI Algorithms
AdaBoost, AlexNet, Autoencoder, Convolutional Neural Network, Long Short-Term Memory Network, Multilayer Perceptron, Multimodal Large Language Model, Regression Analysis, Transformer Model, YOLOAI Applications
AI Chatbot, AI Content Creation, AI Text-to-Image, AI Text-to-Speech, AI-Enhanced Classification, AI-Enhanced Medical Imaging, AI-Generated Code, AIOps, Automatic Speech Recognition, Image Processing, Image-to-Image Translation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Bing AI, GitHub Copilot, Hugging Face, Microsoft 365 Copilot, PyTorch, Replit, Streamlit, TensorFlow, Word2vecAI Models
AlphaCode, BERT, ChatGPT, DALL-E, GPT-3, GPT-4, GPT-J, LLaMA, Midjourney AI, Naive Bayes Classifier, OpenAI Codex, WhisperWhat's included
| Service Tiers |
Starter
$100
|
Standard
$550
|
Advanced
$1,500
|
|---|---|---|---|
| Delivery Time | 4 days | 10 days | 21 days |
Number of Revisions | 3 | 4 | 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 | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$50 - $250
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JF
Johan Henrik F.
Jul 15, 2026
Freelancers: honest review of an AI job-analysis tool (~30 min, $10)
Great and valuable feedback.
RS
Ramon S.
Apr 17, 2026
AI Engineer for Daily Widget Development
I would highly reccomend using Iqra for your projects! She was fast and professional.
About Iqra
Senior AI Solutions Architect | LLMs, CV, MLOps & Agentic Systems
100%
Job Success
Chiniot, Pakistan - 5:11 pm local time
1. What I Build
AI-powered MVPs and SaaS applications
LLM-powered applications and RAG systems
AI agents and intelligent automation workflows
Machine learning and deep learning solutions
NLP and computer vision applications
Recommendation systems
Healthcare AI applications
AI APIs and full-stack AI products
Production deployment and MLOps
2. How I Work
With a BS in Artificial Intelligence, I’ve built my foundation across machine learning, deep learning, NLP, computer vision, reinforcement learning, recommendation systems, generative AI, and MLOps. I don’t see AI as simply plugging an API into an app. I start with the problem, understand what actually needs to be solved, choose the right approach, build and evaluate the AI system, and then turn it into something that works reliably in a real application.
What I Can Handle
• AI/ML Development: Building, training, evaluating, and improving machine learning and deep learning models
• Data & Model Pipeline: Data preprocessing, feature engineering, model selection, training, and evaluation
• LLM Applications: LLM integration, RAG pipelines, embeddings, vector search, and context-aware applications
• AI Agents: Agent workflows, tool integration, reasoning pipelines, and task automation
• NLP & Computer Vision: Building AI systems for language, image, and real-world visual problems
• Model Optimization: Improving model performance, accuracy, reliability, and inference efficiency
• AI Application Development: Turning AI models into usable applications through APIs and backend systems
• Deployment & MLOps: Docker, Kubernetes, model deployment, ML pipelines, monitoring, and production workflows
• End-to-End AI Systems: Connecting the data, model, backend, application, and deployment into one working system
AI Foundation
My foundation comes from a BS in Artificial Intelligence, where I studied AI from both the theoretical and practical side. This includes understanding how models work, how to choose and evaluate the right approach for a problem, and how to take those concepts into real applications. My academic work has covered areas ranging from machine learning and deep learning to NLP, computer vision, reinforcement learning, recommendation systems, knowledge representation and reasoning, healthcare AI, and MLOps.
Selected AI Work
Skin Cancer Detection: Deep learning based medical imaging system with explainability
AI Recommendation System: Personalized recommendations using machine learning
Healthcare AI: AI solutions for medical image analysis and clinical applications
AI Report Matching: Semantic matching and intelligent retrieval for complex report requirements
AI Agents & RAG: LLM based applications with retrieval and intelligent workflows
Steps for completing your project
After purchasing the project, send requirements so Iqra can start the project.
Delivery time starts when Iqra receives requirements from you.
Iqra works on your project following the steps below.
Revisions may occur after the delivery date.
Architecture & Logic Mapping
I will analyze your business logic to design a stateful architecture using LangGraph. This ensures the agents follow a logical flow and includes self-correction loops to prevent infinite cycles.
Custom Tool & API Integration
I will develop custom Python-based tools that allow your agents to interact directly with your internal databases or third-party software (Gmail, Stripe, etc.) securely.