You will get a multi-agent AI SaaS system (LangGraph/CrewAI)
Top Rated
Project details
I build production-ready multi-agent AI SaaS systems that automate complex workflows.
What You Get:
• Fully-functional multi-agent system using LangGraph or CrewAI
• Specialized agents for different tasks with seamless handoffs
• Tool integration for APIs, databases, knowledge bases
• Scalable microservices: Python/FastAPI backend, React frontend, PostgreSQL/MongoDB
• Deployed on AWS/Azure/GCP with Kubernetes orchestration
• Full-stack implementation from design to production
Key Features:
✓ Agent-to-agent communication with state management
✓ Real-time monitoring and error handling
✓ Production-ready: containerized, auto-scalable
✓ Comprehensive documentation
Use Cases:
Customer support automation, business process automation, data analysis, sales enablement, compliance monitoring.
Tech Stack: LangGraph, CrewAI, Python, FastAPI, React, Docker, Kubernetes.
Deliverables: Source code, deployed SaaS app, API docs, deployment guide, 2 weeks support.
Perfect for: Founders building AI-first SaaS, enterprises automating workflows at scale.
What You Get:
• Fully-functional multi-agent system using LangGraph or CrewAI
• Specialized agents for different tasks with seamless handoffs
• Tool integration for APIs, databases, knowledge bases
• Scalable microservices: Python/FastAPI backend, React frontend, PostgreSQL/MongoDB
• Deployed on AWS/Azure/GCP with Kubernetes orchestration
• Full-stack implementation from design to production
Key Features:
✓ Agent-to-agent communication with state management
✓ Real-time monitoring and error handling
✓ Production-ready: containerized, auto-scalable
✓ Comprehensive documentation
Use Cases:
Customer support automation, business process automation, data analysis, sales enablement, compliance monitoring.
Tech Stack: LangGraph, CrewAI, Python, FastAPI, React, Docker, Kubernetes.
Deliverables: Source code, deployed SaaS app, API docs, deployment guide, 2 weeks support.
Perfect for: Founders building AI-first SaaS, enterprises automating workflows at scale.
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System, Software MaintenanceAI Tools
Amazon SageMaker, Azure Machine Learning, Google AutoML, Keras, NVIDIA AI Platform, Open Neural Network Exchange, OpenCV, PyTorch, Sonnet, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$1,990
|
Standard
$3,450
|
Advanced
$4,950
|
|---|---|---|---|
| Delivery Time | 15 days | 25 days | 35 days |
Number of Revisions | 5 | 7 | 9 |
AI Model Integration | |||
Detailed Code Comments | |||
Knowledge Graph | |||
Model Documentation | |||
Ontology | |||
Source Code | |||
Taxonomy |
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Farhan is super talented and well-versed in his field. Highly recommended!
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Aminadav F.
Apr 7, 2025
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Farhan is gifted and resourceful; he worked his magic to make this project work as expected. I highly recommend Farhan!
About Farhan
AI Solutions Architect | AI-First SaaS | Multi-Agent | Full-Stack
100%
Job Success
Karachi, Pakistan - 7:42 am local time
I architect and deploy production-grade AI systems end-to-end. Expert in agentic AI, Model Context Protocol (MCP), and agent-to-agent (A2A) orchestration. Recent work: HIPAA-compliant healthcare platforms (thousands of patients), multi-tenant trading SaaS (millions in volume), voice AI agents, legal document intelligence, energy trading systems.
Core Strengths:
- AI-First Approach: Select optimal solution per problem—classical ML for latency, fine-tuned models (Unsloth/LoRA/QLoRA: Qwen, Gemma, LLaMA) for privacy/control, managed APIs for scale. Decisions grounded in real tradeoffs, not hype.
- End-to-End Ownership: Full stack—AI/ML models, microservices, React/Next.js, cloud infrastructure (AWS/Azure/GCP), DevOps. Database design to production, no handoffs.
- Agentic AI & Multi-Agent Systems: Design sophisticated multi-agent workflows using LangGraph, CrewAI, OpenAI Agents SDK, or custom orchestration. Expert in agent coordination, state management, A2A protocols, seamless handoffs.
- MCP Mastery: Architect MCP-native systems for dynamic tool discovery and integration. Leverage universal standard (97M+ downloads) for rapid integration, reduced deployment friction (11 min vs. 3 days), production reliability.
- Tool Calling & Dynamic Reasoning: Implement context-aware tool invocation for APIs, databases, services. Real-time slot booking, insurance verification, trade execution via intelligent tool chains.
Production Systems Built:
- Healthcare Orchestration: 7+ agents (registration, triage, diagnostics, documentation, compliance) with MCP integration, EMR (Cerner/Oracle), HIPAA-compliant, thousands of interactions. Stack: Python, FastAPI, React, MS SQL, LangGraph, MCP, Azure.
- Voice AI Appointment System: Inbound/outbound calling agent, eligibility screening (40+ dynamic questions), real-time slot booking via tool calls, insurance verification, authorization checks. Stack: Pipecat AI, LiveKit, Twilio, Deepseek, LangGraph, FastAPI, RabbitMQ, React, MS SQL, Azure.
- Legal Intelligence Platform: AI contract analysis, clause extraction, risk flagging, compliance detection. Multi-modal (PDFs, images), RAG semantic search, domain fine-tuning, multi-agent workflow (ingest → classify → extract → analyze → summarize). Stack: Python, FastAPI, React, PostgreSQL, Pinecone, LangGraph, Claude, LoRA.
- Algorithmic Trading SaaS: LSTM/GRU/Prophet forecasting, real-time signals, agentic market analysis, sentiment processing, trade recommendations. Kubernetes auto-scaling, sub-second latency. Stack: Python, FastAPI, React, PostgreSQL, Redis, Kafka, LangGraph, Kubernetes, AWS.
- Energy Trading System: Position limits, surveillance, ICE/CME OTC integration. Agentic risk assessment, pattern recognition, compliance monitoring. Stack: .NET Core, React, PostgreSQL, Kafka, Redis, LangChain, Pinecone, Azure.
Technical Foundation:
Backend: Python/FastAPI, Node.js, .NET Core | Frontend: React, Next.js | Databases: PostgreSQL, MS SQL, MongoDB | Caching: Redis, Kafka | Vector: Pinecone, Milvus, Elasticsearch, ChromaDB | AI Frameworks: LangGraph, CrewAI, OpenAI SDK, MCP, A2A | LLM Fine-Tuning: Unsloth, LoRA, QLoRA, PEFT | LLMs: Claude, Gemini, Deepseek, OpenAI | Cloud: AWS, Azure, GCP + Terraform, Docker, Kubernetes | ML/AI Platforms: Azure AI Foundry, AWS Bedrock, Vertex AI, Hugging Face | Vision/NLP: YOLOv11/v12, BERT, spaCy | Integrations: Twilio, Slack, Airtable, Make, n8n, EMR, trading platforms.
Work Style:
Measure, iterate, optimize. Balance business requirements with technical constraints. Help clients understand tradeoffs. Fluent in technical depth and business translation. Trusted by founding teams, CTOs, architects for validation and time-to-market acceleration.
MS in Data Science + 7 years across healthcare, finance, trading, energy, SaaS. Solve problems holistically—scalability, compliance, performance, UX from day one.
Proven track record: Production-grade, revenue-generating AI systems. Top Rated Plus on Upwork.
Steps for completing your project
After purchasing the project, send requirements so Farhan can start the project.
Delivery time starts when Farhan receives requirements from you.
Farhan works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery and Development