You will get an autonomous multi-agent AI workflow for your business.
Project details
Stop running your business on fragile Zapier connections and basic AI chatbots. If you want to automate complex, multi-step engineering or administrative tasks, you need a resilient Multi-Agent System.
I am an AI Systems Architect specializing in building production-grade autonomous workflows using LangGraph and Python. I will build you a custom "Software Factory" modeled after my proven Brain + Worker architecture.
HOW IT WORKS:
Instead of one AI trying to do everything, the "Brain" agent plans the task and delegates it to specialized "Worker" agents. The system features 5-level self-healing—meaning if an agent encounters an error, it autonomously writes a fix, tests it, and continues the workflow.
PERFECT FOR:
✔ Business Automation: Agents that monitor emails, query databases, and autonomously execute operational tasks 24/7.
✔ Code & Software Generation: Agents that write, test, and deploy code based on your architecture specs.
✔ Data Processing Pipelines: Agents that autonomously extract, clean, and map complex data across multiple platforms.
All tiers include human-in-the-loop safety controls. Let's build something intelligent.
I am an AI Systems Architect specializing in building production-grade autonomous workflows using LangGraph and Python. I will build you a custom "Software Factory" modeled after my proven Brain + Worker architecture.
HOW IT WORKS:
Instead of one AI trying to do everything, the "Brain" agent plans the task and delegates it to specialized "Worker" agents. The system features 5-level self-healing—meaning if an agent encounters an error, it autonomously writes a fix, tests it, and continues the workflow.
PERFECT FOR:
✔ Business Automation: Agents that monitor emails, query databases, and autonomously execute operational tasks 24/7.
✔ Code & Software Generation: Agents that write, test, and deploy code based on your architecture specs.
✔ Data Processing Pipelines: Agents that autonomously extract, clean, and map complex data across multiple platforms.
All tiers include human-in-the-loop safety controls. Let's build something intelligent.
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Software MaintenanceAI Tools
Keras, MLflow, NVIDIA AI Platform, Open Neural Network Exchange, OpenCV, PyTorchAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$450
|
Standard
$1,250
|
Advanced
$3,000
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 21 days |
Number of Revisions | 1 | 3 | 6 |
AI Model Integration | |||
Detailed Code Comments | |||
Knowledge Graph | - | ||
Model Documentation | - | ||
Ontology | - | - | |
Source Code | |||
Taxonomy | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$150 - $700
Additional Revision
+$200
Production Cloud Deployment (Docker)
(+ 3 Days)
+$350
Dirty Data Cleanup & Pipeline Prep
(+ 2 Days)
+$300
Custom Streamlit Web Interface
(+ 4 Days)
+$400Frequently asked questions
About Malik
AI Systems Architect | Multi-Agent LLMs | RAG | Unity AI | Automation
Islamabad, Pakistan - 4:44 pm local time
With 5+ years of professional engineering experience across AI systems, defense R&D, and software products with 500,000+ end-user downloads, I deliver architected solutions — not experiments.
I am one of the few engineers who combines deep LLM/multi-agent orchestration expertise with real Unity simulation and game integration experience. This means I can take on AI projects that require both intelligent decision-making and high-performance real-time environments.
━━━ WHAT I BUILD ━━━
→ Multi-Agent AI Systems (LangGraph, CrewAI) — autonomous pipelines with tool-use, memory, reflection loops, and human-in-the-loop controls
→ Model Training & Fine-Tuning — custom domain adaptation for LLMs and vision models using parameter-efficient fine-tuning (PEFT, LoRA).
→ RAG Pipelines — Hybrid Search (BM25 + vector), Reciprocal Rank Fusion, ChromaDB, FAISS, Pinecone
→ LLM Integration — Claude API, GPT-4o, DeepSeek V3, Groq/Llama 3, prompt engineering, structured outputs
→ AI for Unity — ML-Agents (PPO/SAC), intelligent NPCs, computer vision pipelines (Unity Sentis/ONNX), RL-based agents
→ Production Backends — FastAPI Python servers, async APIs, Celery + Redis task queues, and containerized deployments (Docker).
━━━ PROVEN SYSTEMS ━━━
▶ Foreman (AI Software Factory) — Production-grade multi-agent orchestration system. Brain + Worker architecture, 5-level self-healing, loop detection, HybridRetriever, secure file locking, multi-provider LLM support (DeepSeek, GPT-4o, Claude).
▶ Scrivio (Academic AI Agent) — 7-agent LangGraph pipeline that autonomously writes full academic research papers with verified DOIs and zero hallucinated citations. Stack: FastAPI · Groq · DeepSeek · Celery · Redis · ArXiv · PubMed · Semantic Scholar APIs. 89 backend + 9 E2E tests all passing.
▶ AWC Vision Systems — AI/ML computer vision pipelines integrated directly into Unity runtime for real-time object detection and tracking, built for one of Pakistan's most sensitive defense R&D organizations.
▶ Faris Drone Simulation (POF) — High-fidelity drone flight simulation in Unity for Pakistan Ordnance Factories, modeling real-world aerial dynamics, physics, and flight-path algorithms for defense evaluation.
▶ BioScout — Hybrid RAG agent (BM25 + ChromaDB + DeepSeek Vision) for hallucination-free domain identification and Q&A, built under hackathon conditions.
▶ Bias Detection System (XAI) — Explainable AI pipeline using SHAP analysis to detect
sentiment, gender, and toxicity bias in LLM outputs. Auditable feature-level attribution
for enterprise LLM safety and compliance.
▶ RL Robotic Arm — Reinforcement learning agent (PPO) trained in Unity ML-Agents to
perform stable pick-and-place tasks in randomized environments. Integrated with ROS2
and a Niryo OS2 digital twin.
▶ PINN Research — Physics-Informed Neural Networks applied to the Heimburg nerve
impulse soliton model. Embeds governing physical equations into neural network training
for data-efficient scientific simulation. Paper in submission.
━━━ TECH STACK ━━━
LLMs & Agents: LangGraph · CrewAI · LangChain · Claude API · GPT-4o · DeepSeek · Groq · Llama 3
Training & Fine-Tuning: PyTorch · Hugging Face · LoRA / QLoRA · PEFT · Custom Model Training
RAG & Search: ChromaDB · FAISS · Pinecone · rank_bm25 · Hybrid Search · RRF
Backend & DevOps: FastAPI · Python · Celery · Redis · Docker · AWS/Cloud Deployment · REST APIs
Unity & Simulation: Unity 3D/C# · ML-Agents · Unity Sentis (ONNX) · Reinforcement Learning · ShaderGraph
Other: ROS2 · Digital Twin · SHAP/XAI · PINNs · Computer Vision
━━━ I SPECIALIZE IN ━━━
✔ Agentic business automation — multi-agent workflows that operate 24/7
✔ Domain-specific model adaptation — fine-tuning and deploying custom models for niche industries.
✔ Academic, legal & scientific AI — domain RAG pipelines, PINNs, research agents
✔ Explainable AI (XAI) — SHAP-based bias detection, safe and auditable LLM outputs
✔ AI + Unity integration — intelligent NPCs, ML-Agents, vision pipelines in game/sim environments
All my projects are real, documented, and live on GitHub. I welcome technical interviews and architecture discussions before engagement.
Open to hourly and fixed-price contracts. Let's build something intelligent.
Steps for completing your project
After purchasing the project, send requirements so Malik can start the project.
Delivery time starts when Malik receives requirements from you.
Malik works on your project following the steps below.
Revisions may occur after the delivery date.
Workflow Mapping & Architecture
I map out your business logic and design the multi-agent LangGraph architecture, defining specific roles (e.g., Planner, Executor, Reviewer) for each AI node.
Brain + Worker Development
I build the core Python engine, assigning a "Brain" agent to handle high-level reasoning and "Worker" agents to execute specific tool-based tasks.