Automation & AI Systems
Workflows that do real work in your business — not a demo
Most automation projects die between the demo and the first real customer. I build the other kind. I run Antrix OS — my own automated development platform orchestrating implementation and review loops — in production, every day. That same engineering discipline goes into the automations I build for clients: systems with error handling, observability, and human sign-off, not prompt spaghetti.
Growth & revenue systems
- Content engines: research, scripting, asset generation, and publishing on a schedule — across social, blog, and email
- Ad and creative pipelines: variant generation, hooks, and copy testing at a volume no human team matches
- Outreach and lead generation: prospect research, enrichment, and personalization that doesn't read like a bot wrote it
- Lead routing, follow-up sequences, and CRM automation with human sign-off where judgment matters
Operations automation
- Back-office workflows: document intake, classification, extraction, and routing
- Customer-facing automation — support triage, onboarding, follow-ups — with guardrails
- Event-driven pipelines with queues, schedulers, and workers — the boring parts that make automation reliable
- Claude and OpenAI integrations with evals, fallbacks, and cost controls
Product & engineering systems
- LLM features built into your product: search, summarization, structured extraction
- MCP servers and tool-use architectures that connect models to your real data
- Automated development pipelines: issue pickup, implementation, and code review
- Team enablement: I set up the system, your engineers keep the leverage
Stack & tools
- Claude
- Claude Code
- OpenAI
- Codex
- MCP
- Python
- Node.js
- GitHub Actions
Proof
Where this has worked before
Looking for something adjacent? See all services.
Need automation that survives production?
Tell me what you're working with. You'll get an honest assessment, not a pitch.
I reply within one business day. Currently booking for August 2026.