You will get a custom AI agent built with LangGraph and PydanticAI
Project details
Most AI developers wire together no-code tools and call it an agent. I write the actual code using LangGraph, PydanticAI, and FastAPI.
You will get a custom AI agent built to your exact requirements: a single task agent, a multi-step workflow, or a full multi-agent system with state management and routing. I have built recruitment pipelines, legal research assistants, contract review agents, and document automation systems. All delivered as clean, well documented Python source code you can run locally.
Delivery includes source code, a setup guide, and a README so you can get it running immediately.
You will get a custom AI agent built to your exact requirements: a single task agent, a multi-step workflow, or a full multi-agent system with state management and routing. I have built recruitment pipelines, legal research assistants, contract review agents, and document automation systems. All delivered as clean, well documented Python source code you can run locally.
Delivery includes source code, a setup guide, and a README so you can get it running immediately.
AI Algorithms
Generative Adversarial Network, Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI-Generated Code, Conversational AI, Natural Language Generation, Natural Language Understanding, Sentiment AnalysisAI Development Language
PythonAI Tools
Gradio, Hugging Face, StreamlitAI Models
BERT, ChatGPT, GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$50
|
Standard
$150
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 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 |
Frequently asked questions
About Wisdom
AI Engineer | LangGraph PydanticAI FastAPI RAG Pipelines
Ikorodu, Nigeria - 11:34 pm local time
I build multi-agent systems, RAG pipelines, and AI-powered backends using LangGraph, PydanticAI, LangChain, and FastAPI. If you need an LLM that does more than answer questions, specifically one that routes decisions, manages state, retrieves from your documents, or integrates into a real backend, that is what I do.
Recent builds include a multi-agent routing system where three PydanticAI agents with different capability levels ran as nodes in a LangGraph graph with role-based state routing, and a YouTube-to-document pipeline that processes transcripts into structured Word reports.
What I can build for you: AI agents and multi-agent workflows (LangGraph), RAG systems over your documents or databases (pgvector, PostgreSQL), FastAPI backends with LLM integration, PydanticAI agents with structured outputs, and custom chatbots that go beyond basic Q&A.
I am a Computer Science student at Olabisi Onabanjo University, building production-level AI systems while in school. I work more than 30 hours per week and reply fast.
If you have a problem that needs an intelligent, automated solution, let us talk about it.
Steps for completing your project
After purchasing the project, send requirements so Wisdom can start the project.
Delivery time starts when Wisdom receives requirements from you.
Wisdom works on your project following the steps below.
Revisions may occur after the delivery date.
`1
I review your requirements and confirm the agent scope, inputs, outputs, and LLM provider before starting.
2
I build and test the agent locally, keeping you updated on progress in the workroom.