Resources for the curious clinician and the careful buyer. Whitepapers, blogs, webinars, and conference decks — built for serious readers who want to understand what's under the hood.
Most "AI" tools generate recommendations and stop there. AiM orchestrates a continuous loop — machine intelligence proposes, clinicians validate, action follows, outcomes are measured, and the system learns from every result. The loop continues until the desired result is achieved.
The machine surfaces clinical intelligence drawn from the literature and the patient's own chart.
Clinicians, specialists, committees, payers, and patients challenge, debate, and reach consensus.
Validated decisions become real-world action — at the bedside, in the OR, in policy, in operations.
Did we achieve the result? Every cycle is measured against what matters most.
Outcomes feed back as new teaching data. The machine learns what worked — and what didn't.
Goal = validated outcome
The architecture documents behind every claim on the homepage — written for CMIOs, biomedical informaticists, and clinical AI safety teams.
The full technical specification of the 5-stage loop, the input feeders, the orchestration layer, and the feedback governance that keeps the system honest.
Read the architectureHow the Deep Brain coordinates specialty AI agents, manages conflicts, calculates confidence, and routes high-stakes decisions back to the attending physician.
Read the whitepaperThe cross-institution learning architecture: how every validated decision becomes new teaching data, how privacy is preserved, and how the network compounds value.
Read the whitepaperThe Red Team, Ethics agent, human-in-the-loop pause, audit trail design, and rollback procedures that make AiM safe enough to put in front of a patient.
Read the whitepaperConsidered takes on multidisciplinary review — why bringing the right expertise together sooner helps patients reach informed treatment decisions faster. Visit the blog →
Helping patients reach the right treatment sooner — why bringing multiple clinical perspectives together before critical decisions are made reduces delays and uncertainty.
Read the postHow bringing multiple clinical perspectives together earlier can reduce delays, improve coordination, and help patients reach informed treatment decisions sooner.
Read the postThe challenge is not finding specialists — it's bringing the right expertise together early to identify critical information needs and cut diagnostic delays.
Read the postHour-long deep dives where our clinical team demonstrates the platform with real cases, plus partner panels and AMA sessions.
Our clinical informatics lead walks a GBM case from intake through the Red Team challenge to the human-in-the-loop pause. Q&A after.
RegisterA 45-minute walkthrough of how AiM scores treatment plans across breast, colorectal, prostate, GBM, and pancreatic cancer.
Watch replayThree CMOs and an FDA regulatory consultant on what it takes to deploy multi-agent clinical AI responsibly in a real health system.
Watch replayAn open Q&A with our chief architect on Deep Brain orchestration, Cortex Layer learning, and what we got wrong on the way here.
RegisterPDF slide decks from our keynotes, breakouts, and panels at major healthcare and clinical AI events.
Our keynote on the methodology behind AiM and why we believe coordination — not single-model accuracy — is the right frame for clinical AI.
Download deck (PDF)Live demo of MedBoard with audience-submitted case prompts. Slides + speaker notes.
Download deck (PDF)Breakout session on how AiM operationalizes guideline-concordant care across an oncology service line — with concrete metrics from pilot deployments.
Download deck (PDF)Academic session on human-in-the-loop pause patterns — when to escalate, what to surface, how to log, and what makes interaction design defensible.
Download deck (PDF)Our clinical informatics team responds to every inquiry within one business day — whether you're evaluating, integrating, or just curious about how the loop works in your specialty.