You will get a Multi Agent AI Orchestration Using the New Agent ZERO
Project details
Integrating AI into everything we can is a financial gain. I want to help you do that, and do it quickly, cleanly and efficiently. You have a bunch of tasks you want automated, that will keep you updated as their completed and fix errors as they come up?Solving that, That is My Goal.
AI Algorithms
Deep Belief Network, Large Language Model, Long Short-Term Memory Network, Multilayer Perceptron, Multimodal Large Language Model, Recurrent Neural Network, Self-Organizing Map, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI Text-to-Image, AI-Enhanced Classification, AI-Generated Code, AIOps, Automatic Speech Recognition, Conversational AI, Sequence Modeling, Synthetic Data Generation, Text RecognitionAI Development Language
PythonAI Tools
Bing AI, Copy.ai, GitHub Copilot, Hugging Face, Jasper AI, Microsoft 365 Copilot, NVIDIA AI Platform, PyTorch, Streamlit, TensorFlowAI Models
AlphaCode, BLOOM, ChatGPT, DALL-E, GPT-3, GPT-4, GPT-J, GPT-Neo, LaMDA, LLaMA, Midjourney AI, OpenAI CodexWhat's included
| Service Tiers |
Starter
$2,400
|
Standard
$4,000
|
Advanced
$6,400
|
|---|---|---|---|
| Delivery Time | 10 days | 10 days | 10 days |
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 | - | - | - |
About James
Python Automation & AI Workflow Engineer | Agents, QA
Canadensis, United States - 6:34 pm local time
I design systems that don’t just “work once,” but are structured, debuggable, and resilient. My work emphasizes clear control flow, failure recovery, background processing, and scalability.
What I build
Python automation & backend systems
Agent workflows with structured planning, validation, and tool routing
AI-powered pipelines (RAG, memory, orchestration — model-agnostic)
Background workers with retries, backoff, and dead-letter handling
Async API orchestration using asyncio
Cron-based unattended automation
Reliability layers (error classification, graceful degradation)
Example systems I’ve built
An agent orchestration platform with explicit state machines, structured planning, retries, and fallback behavior
A retrieval-augmented knowledge pipeline (RAG) with chunking, retrieval, and safe fallback logic
A conversational memory engine with summarization and context-budget enforcement
Background job workers that process queued tasks asynchronously and recover from transient failures
Scheduled automation that runs unattended with logging and auditability
How I work
Clean, modular Python code
Strong emphasis on logging and debuggability
Systems designed to run unattended without babysitting
Clear communication and incremental delivery
If you need automation that works reliably, or an AI workflow that doesn’t behave unpredictably, I can help.
Steps for completing your project
After purchasing the project, send requirements so James can start the project.
Delivery time starts when James receives requirements from you.
James works on your project following the steps below.
Revisions may occur after the delivery date.
Client purchases the project send requirements
I take the clients information and explain roughly what we need or dont need to complete this project. The scope is defined.
Initial Draft is revised
Skeleton of project is put together along the line of the Initial Draft We revise and discuss any possible changes and lock our scope down and begin the real building