Infrastructure for AI content and film production at scale. Built by someone who's also been the CMO responsible for what comes out the other end.
Most AI engineers build pipelines. Most CMOs know what good output looks like. Almost nobody holds both.
I've run marketing at the CMO level — across multi-million MRR orgs in fintech, crypto, gaming, and consumer SaaS. I've also been on the frontier of generative AI since ChatGPT's first week: frontier models, local LLMs, training pipelines, model routing in production.
The systems I build are calibrated to outcomes before the first line of code runs.
An AI cinematic content platform built from scratch. Product, infrastructure, brand, AI model integrations, and the mass automation pipeline that produces every image and video on the platform. Consumer scale. No team.
End-to-end pipeline builds for content and film production at scale. Multi-model routing, character development, LoRA training, generation automation, QC gates, CDN delivery. For studios and production companies that need unattended output at quality.
Custom AI agent stacks built on Claude API + MCP servers. Vector context memory. Orchestration across tools and data sources. 55 live workflows and 13 deployed agents running in production. For companies that need internal AI infrastructure without hiring a full team.
Systems designed around outcomes. I've been the CMO responsible for what pipelines produce. I build for distribution — search engines, AI answer engines, audiences. Technical depth and strategic context in one engagement.
Generated output. No human per asset.
ChatGPT week 1 → frontier models → local LLMs → production infrastructure
The team is the machine.
The machine doesn't need managing.
If the brief fits, I respond fast. One conversation before any commitment.