Mast Labs builds AI infrastructure, domain intelligence, and operating models for regulated environments. Engagements when you need clarity. Infrastructure when you need AI to work.
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Most AI infrastructure moves data. The hard part is what happens in between. The taxonomy, the ontology, the classification models that turn raw data into the language your business actually uses. That is what we build.
Multi-tenant, event-driven platforms. PHI-safe, governed, observable. Architecture, data, and orchestration designed for regulated environments.
Proprietary taxonomy, ontology, and classification systems. Purpose-built small language models trained on your domain, not the open internet. The systems that decide and route.
Audit trails, PHI firewalls, policy enforcement. Built into the platform, not bolted on after. Compliance as a system property, not a project.
Notes on building production AI in regulated environments. Long-form lives on LinkedIn.
Tools automate tasks. Agentic systems understand purpose. The difference is whether intent, evidence, and accountability are wired into the architecture before autonomy is introduced.
Read on LinkedIn →Most teams don't fail because they chose the wrong model. They fail because the right questions were never asked early enough, before assumptions hardened into data structures and workflows.
Read on LinkedIn →AI at the application layer reduces task time. AI at the operating layer reduces economic drag. Operating models decide whether AI spend behaves like an expense or an asset.
Read on LinkedIn →Mast Labs is taking on a small number of fractional and advisory engagements. If you are building or scaling AI in a regulated environment, let's talk.
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