AI Automation & Agentic Systems
AI that does real work in your business — not a demo
Most AI projects die between the demo and the first real customer. I build the other kind. I run Antrix OS — my own multi-agent engineering platform orchestrating Claude Code, Codex, and automated 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 checkpoints, 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 checkpoints 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 AI reliable
- Claude and OpenAI integrations with evals, fallbacks, and cost controls
Agentic & product engineering
- LLM features built into your product: search, summarization, structured extraction
- MCP servers and tool-use architectures that connect models to your real data
- Multi-agent development systems: automated issue pickup, implementation, and PR 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 AI that survives production?
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