Most AI stops at the demo. I ship the rest.

Healthcare and finance need AI that works with their data, not around it.

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 Factory

Autonomous AI agents that process documents, route data, and execute workflows without manual intervention. Scales without scaling the team.

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.

Your organization already has the answers — buried in PDFs, internal wikis, legacy databases. Search that surfaces them with citations, not hallucinations.

Clinical Terminology MCP

Verified medical coding — SNOMED CT, ICD-10, RxNorm — available locally inside your AI assistant. No data leaves your network.

MLLP Server

HL7 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 Automation

The 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.

One conversation. No handoffs.