AI Enablement for SMB
Cloud AI products send your data to someone else's infrastructure. For regulated industries -- healthcare, legal, finance -- that's not a privacy consideration, it's a compliance one. We deploy private AI into your environment: on your hardware, under your control, with routing you decide. Consulting and staff training are available on their own.
What You Get
Plain-language advice for owners and managers making their first AI decisions: which tools fit the work, what data may go into them, and what to leave alone. Available as a fixed-scope assessment, by the hour, or on retainer.
On-site talks for your staff, beginner to intermediate. Each is one hour, for a group of 5 to 200. Three to choose from: Your Staff Is Already Using AI, for all staff; Five Decisions Before Your Office Buys Any AI, for owners and managers; and How AI Gets It Wrong, for staff who already use it. Content is adjusted to the engagement.
Most AI projects fail because the use case was chosen based on what's possible, not what's useful. We start by identifying where AI creates measurable workflow value for your specific practice -- and which use cases aren't worth the effort.
Model inference runs on hardware installed at your site. Every configuration is built and tested first in our own lab, Rondthaler Labs.
The right model for the task -- not the largest one that'll fit on the hardware. We match model capability to use-case requirements, configure inference parameters for your workload, and validate output quality before production.
AI grounded in your actual documents -- clinical protocols, firm templates, policy manuals, case files. Not a general-purpose chatbot. Answers sourced from your data, with citations you can verify.
AI wired into the tools your staff actually uses -- not a standalone interface they have to remember to open. Integration with document management, EHR workflows, or internal portals depending on your environment.
Ongoing model availability monitoring, performance tracking, and update management. AI infrastructure maintained like any other production system -- not deployed and abandoned.
How It Works
We interview staff and review workflows to identify where AI creates real value -- time saved, accuracy improved, or capacity freed. Use cases ranked by impact and implementation complexity before any infrastructure decision.
Hardware requirements sized to the selected models and workload. Existing infrastructure assessed for suitability. Procurement guidance provided if new hardware is required.
Model deployment, inference stack configuration, and integration with selected workflows. Staff training on interaction patterns and output validation before go-live.
Monitoring in place, runbooks documented, and ongoing support defined. The system runs as production infrastructure -- with the same operational discipline applied to everything else we manage.
Who This Is For
HIPAA doesn't prohibit AI. It requires a Business Associate Agreement with any vendor that handles PHI on your behalf, before the PHI reaches them. Here the model runs in your environment, on your terms.
Contract review, document summarization, precedent research -- these are high-value AI use cases. They're also use cases where sending client files to a third-party API raises confidentiality obligations your firm has to answer for.
Cloud AI products often aren't an option. Private AI infrastructure usually is. If you've been told your industry can't use AI, the more accurate statement is that your industry can't use most AI products as deployed.
If you're the one vetting this
The architecture, the routing rule, and the governance model behind this service are published at rondthaler.dev.
The service as designed, and the R&D Log that tracks the build.
When a workload may be routed to an outside model, and the conditions it has to meet first.
The six-layer governance picture, revised for a small regulated practice.
AI engagements start with use-case discovery -- identifying where AI creates measurable value in your specific workflows before any infrastructure decisions are made.
