I design and build autonomous and semi-autonomous AI agent systems that perform multi-step tasks — research, data processing, decision-making, reporting — with human-in-the-loop controls where needed.
What you get:
• Custom AI agent system tailored to your workflow
• Orchestration logic: sequential, parallel or conditional task execution
• Tool integrations — web search, APIs, databases, file systems
• Monitoring and logging so you know what the agent did and why
• Human approval gates for high-stakes decisions
• Documentation and handoff
Use cases:
• Research agents — automated market research, competitor monitoring, lead enrichment
• Data processing agents — ingest, clean, analyze and report across multiple sources
• Content generation pipelines — multi-step content creation with review checkpoints
• Customer outreach automation — personalized messaging at scale
• Internal ops agents — ticket routing, report generation, status monitoring
Tech stack: LangChain, custom Python agent frameworks, OpenAI API, Claude API, N8N, Zapier, MCP (Model Context Protocol), Playwright for web interaction, FastAPI for orchestration.
I've built agent systems that run daily in production — scraping, scoring, deciding and reporting without manual intervention. I focus on reliability (error prevention, retry logic, graceful degradation) not just demos.
Every agent I build has clear logging, is testable, and can be extended by your team.