You will get OpenClaw AI Agent System with Routing, Guardrails and Monitoring
Project details
A fully operational multi-agent OpenClaw system featuring an Orchestrator that intelligently assigns tasks to specialized Task Agents, with built-in safety mechanisms suitable for production environments. This project emphasizes disciplined engineering: well-defined agent roles, structured routing and escalation strategies, a tool access control matrix, and approval steps for sensitive operations. Workflows are executed end-to-end with consistent test coverage, transparent execution tracking, and robust handling of edge cases such as missing inputs, tool failures, or communication interruptions. For scenarios where complex workflows require reliability, controlled tool usage, and clear agent accountability, this solution provides a scalable and extensible architecture.
AI Algorithms
Autoencoder, Convolutional Neural Network, Deep Belief Network, Feedforward Neural Network, Generative Adversarial Network, Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI Text-to-Image, AI Text-to-Speech, AI-Enhanced Classification, AI-Generated Code, AI-Generated Video, Conversational AI, Natural Language Generation, Natural Language Understanding, Neural Machine TranslationAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Hugging Face, Jasper AI, Microsoft 365 Copilot, Replit, Streamlit, TensorFlowAI Models
BERT, ChatGPT, DALL-E, GPT-4, LLaMA, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$250
|
Standard
$900
|
Advanced
$2,500
|
|---|---|---|---|
| Delivery Time | 2 days | 5 days | 20 days |
Number of Revisions | 1 | 2 | 3 |
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 |
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MA
Marta A.
Jul 13, 2026
AI Automation Expert needed.
It was a pleasure working with this freelancer. Communication was smooth, deadlines were respected, and the overall collaboration was professional and efficient. I would definitely consider working together again in the future. Recommended!
About Waqar
AI Automation | AI Agents | LLM | RAG | n8n
Peshawar, Pakistan - 8:38 am local time
I specialize in LLM powered agents, RAG pipelines, and multi-agent automation for companies building AI into their products or workflows not just demos, but systems that actually run in production.
🤖 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 & 𝐕𝐨𝐢𝐜𝐞 𝐀𝐠𝐞𝐧𝐭𝐬
🔹 Agent frameworks: LangChain, LlamaIndex, OpenAI Agents SDK
🔹 Multi-agent orchestration: CrewAI, AutoGen
🔹 Voice AI: Amazon Polly, Deepgram, Rasa, VAPI
🧠 𝐋𝐚𝐫𝐠𝐞 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐌𝐨𝐝𝐞𝐥𝐬
🔹 APIs & hosted models: OpenAI GPT-4o, Anthropic Claude, Amazon Bedrock
🔹 Open-source models: LLaMA 3, Mistral, Mixtral, Falcon, Gemma
🔹 Local model deployment: Ollama
📚 𝐑𝐀𝐆 & 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐚𝐥
🔹 Retrieval frameworks: LangChain, LlamaIndex
🔹 Vector databases: FAISS, Pinecone, Qdrant, ChromaDB
🔹 RAG pipelines with semantic search, document chunking, and context retrieval
⚡ 𝐋𝐋𝐌 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧
🔹 Prompt engineering (multi-turn, few-shot, zero-shot)
🔹 Inference optimization using vLLM and TensorRT-LLM
🔹 Model quantization: AWQ, GPTQ, GGUF
🔹 LLM evaluation pipelines and dataset generation
⚙️ 𝐁𝐚𝐜𝐤𝐞𝐧𝐝 & 𝐀𝐏𝐈 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭
🔹 Python backend: FastAPI, Flask, Django
🔹 API development: REST APIs, GraphQL APIs
🔹 Databases: PostgreSQL, MySQL, MongoDB, Redis
🔹 Infrastructure: Docker, Kubernetes, AWS EC2, S3, Nginx
☁️ 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 & 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞
🔹 Cloud platforms: AWS, GCP
🔹 AI deployment: SageMaker, RunPod, Vercel
🔹 Containerization and scalable AI backend architecture
💡 𝐖𝐡𝐚𝐭 𝐈 𝐁𝐮𝐢𝐥𝐝 𝐟𝐨𝐫 𝐂𝐥𝐢𝐞𝐧𝐭𝐬
✔ AI customer support agents
✔ AI Agents for Social Media
✔ RAG chatbots trained on company knowledge
✔ AI automation workflows
✔ Multi-agent AI systems
✔ Voice AI assistants
✔ AI-powered SaaS features
Ready to turn your AI idea into a production system? Message me your use case and I’ll send a short implementation plan and next steps.
Steps for completing your project
After purchasing the project, send requirements so Waqar can start the project.
Delivery time starts when Waqar receives requirements from you.
Waqar works on your project following the steps below.
Revisions may occur after the delivery date.
Project Scope & Requirements Review
Review client goals, workflow needs, tools, and approval rules. Define agent roles, orchestration logic, integrations, and success criteria before development begins.
Requirement Analysis
Review client goals, documents, and technical needs. Define scope, success criteria, and confirm deliverables before starting development.