AI Agent Development

    I build custom AI agents, copilots, and intelligent assistants using Python, OpenAI, Claude, and LangChain — tailored to your business data, workflows, and product.

    Types of AI Agents I Build

    Custom AI Agents

    Autonomous agents that reason, plan, and execute multi-step tasks — browsing the web, querying databases, calling APIs, and making decisions without constant human input.

    RAG Systems

    Retrieval-Augmented Generation systems that ground AI answers in your proprietary data — documents, databases, and knowledge bases — for accurate, context-aware responses.

    AI Copilots & Assistants

    Embedded AI assistants for your product or internal tools — answering questions, drafting content, summarizing data, and guiding users through complex workflows.

    Multi-Agent Orchestration

    Orchestrate multiple specialized AI agents working together to complete complex, multi-step business tasks that a single agent cannot handle alone.

    What You Get

    Custom AI agent architecture
    Python / LangChain / LangGraph backend
    OpenAI / Claude API integration
    RAG pipeline with vector database
    Tool & function calling setup
    API & webhook integrations
    Prompt engineering & optimization
    Memory & context management
    Monitoring & observability
    Documentation & handover

    Common Questions

    What AI models do you build with?

    Primarily OpenAI (GPT-4o, o1) and Anthropic Claude (claude-sonnet-4-6, claude-opus-4). I choose the model based on your use case — cost, latency, context window, and reasoning requirements all factor in.

    What is RAG and do I need it?

    Retrieval-Augmented Generation (RAG) lets the AI answer questions using your specific data — your documents, database, product catalog, or knowledge base — rather than just its training data. If your AI needs to know things specific to your business, you likely need RAG.

    How do you keep AI responses accurate and on-brand?

    Through careful prompt engineering, retrieval grounding (RAG), output validation, guardrails, and evaluation pipelines. I also set up monitoring so you can catch and correct drift over time.

    Can you integrate the AI agent into my existing product?

    Yes. I build agents as API services that plug into your web app, mobile app, CRM, or internal tools via REST API or webhooks — no full rebuild required.

    How long does it take to build a custom AI agent?

    A focused AI assistant or copilot takes 2–4 weeks. A multi-agent system with RAG, custom tools, and full integration is typically 6–10 weeks.

    Let's Build Your AI Agent

    Free 30-minute call. I'll review your use case and design the right AI architecture for your product.

    Book Free Consultation