Most AI stops at the demo. I ship the rest.
AI implementation and deployment for regulated industries. Data pipelines, knowledge search, task-specific agents, workflow automation, and autonomous dark factory systems.
Deploy
AI Implementation
The AI software is cheap. Making it work in a messy, real-world business is the hard part. Data readiness, system integration, production deployment.
Dark FactoryAutonomous AI agents that process documents, route data, and execute workflows without manual intervention. Scales without scaling the team.
Data & Search
Clinical & Financial Data
Most AI tools ignore the hard part: getting structured data out of messy clinical and financial systems. The model is only as good as what you feed it.
Knowledge SearchYour organization already has the answers — buried in PDFs, internal wikis, legacy databases. Search that surfaces them with citations, not hallucinations.
Clinical Terminology MCPVerified medical coding — SNOMED CT, ICD-10, RxNorm — available locally inside your AI assistant. No data leaves your network.
MLLP ServerHL7 v2.x messages over MLLP, parsed and routed. One binary, no runtime dependencies, no integration engine license.
Agents & Automation
AI Agents
An agent without guardrails is a liability. Task-specific agents with defined boundaries, human-in-the-loop where it matters. No autonomous black boxes.
Workflow AutomationThe bottleneck is rarely the algorithm. It's the manual steps between systems — data routing, status checks, approval workflows.
Who this is not for
You need a team of ten.
I am one engineer. If the project requires a department, this is not the right fit.
You want a demo, not a product.
I do not build proof-of-concepts that end at the slideshow. Production or nothing.
You are not in a regulated industry.
Healthcare, finance, compliance. If none apply, you will overpay for guardrails you do not need.
You need 24/7 support SLAs.
One person cannot promise round-the-clock availability. If uptime contracts matter, hire a team.