You will get agentic AI system with tool calling & dynamic workflows
Top Rated
Project details
I build agentic AI systems where agents autonomously invoke tools, make decisions, and adapt workflows in real time.
Tool Calling Power:
Agents move beyond Q&A—they invoke APIs, query databases, trigger business logic, and access external services with context-aware decision-making. Dynamic workflows adapt execution paths based on agent reasoning and outcomes.
What You Get:
• Agents with sophisticated tool-calling capabilities
• Dynamic workflow orchestration adapting to tool results
• Integration with your APIs, databases, business systems
• Context-aware decision-making and autonomous error handling
• Full-stack: backend agents, frontend dashboard, admin controls
• Audit trail of all agent decisions and tool calls
Key Features:
✓ Tool registry with dynamic discovery and invocation
✓ Conditional workflows based on tool outcomes
✓ Automatic retry and resilience mechanisms
✓ Human-in-the-loop escalation workflows
✓ Multi-step reasoning with chained tool calls
Tech Stack: LangGraph, Python, FastAPI, React, PostgreSQL, Redis.
Examples: Insurance claims evaluation, e-commerce order automation, healthcare AI scheduling.
Tool Calling Power:
Agents move beyond Q&A—they invoke APIs, query databases, trigger business logic, and access external services with context-aware decision-making. Dynamic workflows adapt execution paths based on agent reasoning and outcomes.
What You Get:
• Agents with sophisticated tool-calling capabilities
• Dynamic workflow orchestration adapting to tool results
• Integration with your APIs, databases, business systems
• Context-aware decision-making and autonomous error handling
• Full-stack: backend agents, frontend dashboard, admin controls
• Audit trail of all agent decisions and tool calls
Key Features:
✓ Tool registry with dynamic discovery and invocation
✓ Conditional workflows based on tool outcomes
✓ Automatic retry and resilience mechanisms
✓ Human-in-the-loop escalation workflows
✓ Multi-step reasoning with chained tool calls
Tech Stack: LangGraph, Python, FastAPI, React, PostgreSQL, Redis.
Examples: Insurance claims evaluation, e-commerce order automation, healthcare AI scheduling.
AI Algorithms
AlexNet, Gated Recurrent Unit, Generative Adversarial Network, Large Language Model, Long Short-Term Memory Network, Multimodal Large Language Model, Recurrent Neural Network, Transformer Model, Variational Autoencoder, YOLOAI Applications
AI Chatbot, AI Content Creation, AI Text-to-Image, AI Text-to-Speech, AI-Enhanced Medical Imaging, AI-Generated Art, AI-Generated Music, AI-Generated Video, Anomaly Detection, Facial Recognition, Image Recognition, Speech SynthesisAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Gradio, Hugging Face, Jasper AI, PyTorch, Replit, Streamlit, TensorFlow, Word2vecAI Models
BERT, ChatGPT, DALL-E, Dolly, GPT-3, GPT-4, GPT-Neo, LLaMA, Midjourney AI, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$990
|
Standard
$1,990
|
Advanced
$2,990
|
|---|---|---|---|
| Delivery Time | 10 days | 20 days | 30 days |
Number of Revisions | 3 | 4 | 4 |
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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Farhan is super talented and well-versed in his field. Highly recommended!
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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 - 2:53 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