You will get Private Multi-Agent Workspace Automation
Project details
Organizations want autonomous multi-agent workflows to reduce manual overhead, but sending sensitive data to public cloud APIs creates major risks around privacy, compliance, and unpredictable token costs.
I build secure Multi-Agent Workspace Frameworks that run entirely on private infrastructure using open-source LLMs like Llama 3 and Mistral. Powered by high-concurrency FastAPI microservices, the system ensures complete data sovereignty and local execution.
What’s Included:
• Multi-Agent Core: LangChain/LangGraph workflows for autonomous task routing and reasoning.
• Secure Ingestion: Context-aware vector storage using Qdrant or Pinecone with strict access controls.
• MLOps Packaging: Containerized backend services with Docker/Kubernetes support for local GPU clusters.
Why This Architecture?
1. Full Data Sovereignty: Built with a cyber security-first mindset to reduce prompt injection and data leakage risks.
2. Proven Scalability: Experience building systems serving 10,000+ active users with high availability.
3. Zero API Costs: Quantized local inference with vLLM removes dependency on third-party API billing.
I build secure Multi-Agent Workspace Frameworks that run entirely on private infrastructure using open-source LLMs like Llama 3 and Mistral. Powered by high-concurrency FastAPI microservices, the system ensures complete data sovereignty and local execution.
What’s Included:
• Multi-Agent Core: LangChain/LangGraph workflows for autonomous task routing and reasoning.
• Secure Ingestion: Context-aware vector storage using Qdrant or Pinecone with strict access controls.
• MLOps Packaging: Containerized backend services with Docker/Kubernetes support for local GPU clusters.
Why This Architecture?
1. Full Data Sovereignty: Built with a cyber security-first mindset to reduce prompt injection and data leakage risks.
2. Proven Scalability: Experience building systems serving 10,000+ active users with high availability.
3. Zero API Costs: Quantized local inference with vLLM removes dependency on third-party API billing.
AI Algorithms
Autoencoder, Convolutional Neural Network, Feedforward Neural Network, Generative Adversarial Network, Large Language Model, Long Short-Term Memory Network, Multimodal Large Language Model, Regression Analysis, Transformer Model, YOLOAI Applications
AI Chatbot, AI-Enhanced Classification, Image Processing, Image Recognition, Natural Language Generation, Neural Machine Translation, Object Detection, Sentiment Analysis, Synthetic Data Generation, Text Recognition, Time Series Analysis, Time Series ForecastingAI Development Language
PythonAI Tools
Hugging Face, NVIDIA AI Platform, PyTorch, Streamlit, TensorFlow, Word2vecAI Models
BERT, ChatGPT, GPT-4, LLaMA, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$1,500
|
Standard
$6,000
|
Advanced
$12,000
|
|---|---|---|---|
| Delivery Time | 10 days | 15 days | 60 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 | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$500 - $5,000
Additional Revision
+$150About Abbas
Senior AI Engineer & Secure Architect
Rennes, France - 2:33 pm local time
I am an AI Systems Engineer specializing in building production-ready, secure Multi-Agent Orchestrations, advanced RAG architectures, and custom open-source model deployments. With a background blending an MSc in Cyber Security and a BS in AI, I bridge the gap between advanced machine learning and ironclad enterprise security.
What I bring to your project:
• Scale & Concurrency: Built a mission-critical platform managing secure data for 10,000+ users with 100% uptime under peak loads.
• Security & Trust: Specialized in Zero-Trust AI architecture, avoiding data leakage, securing vector databases, and ensuring HIPAA/GDPR compliance.
• Cost Optimization: Transitioning clients away from expensive closed-source API dependencies to hyper-optimized local deployments.
--- My Core Capabilities ---
1. ADVANCED RAG & MULTI-AGENT SYSTEMS
• GraphRAG, Semantic Chunking, Hybrid Vector Search (Pinecone, Chroma, Qdrant)
• Autonomous Multi-Agent Workflows & Team Simulations (LangChain, LangGraph, CrewAI)
• Context-aware retrieval systems with zero-hallucination guardrails
2. SECURE AI ARCHITECTURE & INFRASTRUCTURE
• Secure data parsing pipelines (SQL, legacy systems, messy enterprise documents)
• FastAPI microservices deployed inside containerized environments (Docker, Kubernetes)
• Localized, off-grid server engineering for high-sensitivity workflows
3. DEEP LEARNING & COMPUTER VISION
• Specialized 2D/3D volumetric segmentation and medical image processing (MONAI, nnU-Net)
• High-concurrency object detection and video streaming pipelines (YOLO) deployed on industrial edge hardware
--- Selected Career Highlights ---
• Co-authored IEEE Publication on Neural Machine Translation (improved performance by 65%).
• 1st Prize Winner: ActInSpace 2026 International Space Innovation Hackathon (Edge-Computing AI Solution).
• Engineered a centralized Autonomous Multi-Agent SOC System for automated log threat hunting and mitigation.
Let's turn your AI vision into a production-grade asset. Click "Invite to Job" to schedule a brief discovery call.
Steps for completing your project
After purchasing the project, send requirements so Abbas can start the project.
Delivery time starts when Abbas receives requirements from you.
Abbas works on your project following the steps below.
Revisions may occur after the delivery date.
Original brief discussion
Discussing the client's requirements and expectations and deciding a clear plan of action