39 years of knowledge-driven healthcare technology, now converging with AI to help independent practitioners capture what makes their care unique — and scale it.
See What You GetSince 1987, we've worked alongside independent practitioners who know their patients better than any algorithm — from early expert systems and knowledge engineering, through clinical education and digital therapeutics, to today's mission: building AI tools that learn how you practice, not the other way around.
You've spent years developing how you assess, communicate, and make decisions. We build systems that capture that expertise — the patterns, instincts, and reasoning that no EHR template can hold.
AI tools designed around how you actually work — not how a hospital system thinks you should. Technology that extends your reach without flattening what makes your care different.
Patient-facing content systems that preserve your voice, your tone, and the relational intelligence your patients trust — scaled across digital platforms without losing the human touch.
Four tools, one pipeline. WisdomIQ extracts the judgment a clinician cannot state directly. ResearchIQ holds the evidence they actually trust. The Knowledge Base governs both in one store. Knowledge Chat turns it into a conversation that answers in their voice — and it is running today.
We start by understanding how you actually practice — your clinical reasoning, the way you talk to patients, the decisions that define your care.
Using DKA methodology, we build a structured model of your expertise — the patterns, instincts, and communication style that make your practice yours.
AI tools, content systems, and digital platforms are designed around your knowledge model — not a generic template you have to adapt to.
Your expertise reaches more patients, your content sounds like you, and your practice grows — without losing the identity that built it.
Not a chatbot trained on things you have written — a structured account of how you decide, held as small units you can read and correct. Every one of them shown back to you in your own words before it is kept. It is yours, and you can export all of it at any time.
Conversations, assessments and education that answer in your voice and refuse the questions you would refuse. Your safety register decides where they stop. Nothing reaches a patient until you say it can.
The by-product most practitioners end up valuing most: your exceptions, your boundaries and the conditions under which you break your own rules, written down for the first time — in a form you can hand to a colleague, a successor, or a court.
Two or three short sessions a week, twenty to forty minutes each, for about six weeks — answering real situations from your own field and correcting what comes back. No scheduled calls and nothing to keep up with. After that it goes quiet: a few minutes a week, for as long as you keep practising.
We start with a single practitioner and one application rather than a platform. If it does not sound like you by the end, it does not ship — and you keep everything either way.
What these systems will never do, and who owns what you put in ›
DKA is a methodology for human-AI partnership, derived rather than theorized. It came out of 39 years of building clinical and behavioral programs alongside practitioners — the patterns that survived one technology generation after another, and the ones that did not. It captures how you actually think, communicate, and make clinical decisions, creating living knowledge structures that evolve alongside your practice.
Its premise is that the AI learns your intelligence — your clinical reasoning, your communication style, your way of building trust with patients. That is where the work starts. Whether the methodology holds up as a method, rather than as an accurate description of what already worked, is an open question, and a pilot is how it gets answered.
The method carries obligations, and we set them out in full — what is reviewed, what these systems refuse to do, and who owns the material.
The culmination of 39 years of work at the intersection of healthcare, knowledge systems, and artificial intelligence. This book documents the DKA methodology — how to build AI systems that think with practitioners, not for them. Currently in development.
This is a small practice and I intend to keep it that way. I take on a few projects at a time and I choose them for how interesting the problem is, not for how large the client is. That means I am not the right fit for everyone — and I would rather we establish that early than late.
What I bring is thirty-nine years of doing this and the confidence to build and execute, not just advise. I am not competing with the large platforms on scale, and I am not trying to. I am competing on whether the thing actually works better for the practitioner using it, which in this field is what decides it.
— Tom Conant
If that sounds like your kind of problem, a few questions help me understand what you have in mind before we speak. It takes about a minute.
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