I build custom AI agents and RAG-powered assistants that understand your business information, retrieve relevant knowledge, connect to existing systems, and perform authorized tasks through tools and APIs.

Whether you need a customer-facing assistant, an internal knowledge chatbot, or an AI agent that works with your CRM, inventory, or business database, I develop practical solutions designed for real-world use.

With 10+ years of full-stack engineering experience, I combine AI capabilities with reliable backend architecture, secure integrations, and production-ready applications.

Custom AI agents: Intelligent assistants that use tools, call APIs, and execute controlled multi-step workflows.

RAG knowledge assistants: Search and answer questions using company documents, PDFs, websites, and knowledge bases.

AI-powered business intelligence: Query operational data using natural language to understand sales, inventory, customer information, and other business metrics.

Customer support and sales assistants: Build conversational assistants for websites, internal applications, and WhatsApp Business.

MCP and tool integrations: Connect AI assistants with existing applications, databases, and external services using MCP or custom tools.

Multi-step AI workflows: Build context-aware interactions, structured tool execution, conversation management, and human approval where needed.

Claude, OpenAI, LangChain, LangGraph, MCP, Node.js, TypeScript, Next.js, PostgreSQL, pgvector, and AWS.

Discovery: Understand your use case, data sources, user requirements, and desired assistant capabilities.

Architecture: Design the AI workflow, retrieval strategy, tool integrations, and security controls.

Development: Build the assistant, integrate your knowledge sources and systems, and implement conversation flows.

Evaluation: Test response accuracy, retrieval relevance, tool behavior, and failure handling.

Deployment: Integrate the assistant into your application or selected communication channel and provide documentation.

A custom AI assistant based on the agreed use case

Integration with selected documents, databases, or business APIs

RAG-based knowledge retrieval or agentic tool execution as required

Conversation context and appropriate access controls

Testing, deployment support, and documentation

I built a production inventory and accounting platform with a Claude-powered AI assistant connected to live business data through a custom MCP server. The business owner can ask questions about inventory, sales, customer balances, and profitability and receive answers grounded in real records.

I've also developed a real estate AI assistant that supports property inquiries through WhatsApp and the web, combining conversational AI, property search, and lead management.

Want an AI assistant that understands your business and works with your existing systems? Share your use case, and I'll help define an appropriate technical approach.