Evidence-Led Innovation. Built on Clinical Rigor
Our proprietary architecture is the result of deep academic research into the complexities of clinical data—ensuring safety remains at the center of our development.
Addressing Human Variance →
Before writing our first line of production code, we conducted a foundational study in partnership with the University of Galway and Munster Technological University. We analysed 6,000+ data points to understand a fundamental truth: even experienced clinicians disagree 77.1% of the time.
This research became our Developmental North Star. It taught us that "Black Box" AI is insufficient for healthcare. Instead, we built a system designed to handle the nuances, contradictions, and subjectivity of real-world medicine.
The Governance Timeline
2023-2024 | Foundational Research (Completed)
Qualitative analysis of 6,000+ data points to identify failure modes and human-evaluator disagreement patterns.
Late 2024
Architectural Shift (Completed) Transitioned to the "Assistant + Judge" model to provide a rules-based safety layer over AI outputs.
Active | National Evaluation (In Progress)
Active | Enterprise Pilot & Local Assurance (Pre-Deployment)
Independent evaluation with Health Innovation Hub Ireland (HIHI) & the HSE within live adult outpatient pathways.
Implementing the Beacon Protocol to establish site-specific statistical safety baselines.
Verified Automation: The Assistant + Judge
Alto reads every referral document, regardless of format, and transforms it into a structured, prioritised action. Think of it like a highly trained medical administrator who never sleeps, never mis-types, and flags every urgent case immediately. It works in three stages, each with a specific job.
The Assistant reads the referral, extracts all clinical data, checks it against the hospital's own rules, and proposes the next action e.g. route to consultant, request more info, flag urgency.
The Judge is an independent QA layer that audits every single output from the Assistant. Catches errors. Flags low-confidence cases for a human to check. This is why we can offer 99%+ accuracy.
The Outcome: If the system identifies a high-risk conflict or clinical uncertainty, it does not "guess." Instead, it flags the file for human review, providing a transparent evidence trail for every decision.
The Beacon Protocol – Continuous Evidence
Safety Baseline Study
We validate 400+ cases specific to your clinic’s unique case mix to calibrate the “Assistant” and "Judge" module.
Silent Shadow Mode
Alto processes live referrals in the background, comparing its "Silent Predictions" against your clinicians’ actual decisions without influencing live workflows.
The Evidence Phase
Once local alignment is confirmed, the system moves to "Helper Phase," continuing to generate performance data until we hit a 1,000+ case validation milestone.
Academic Rigour & Validation
Alto is committed to radical transparency. By categorising error taxonomies—identifying missed, hallucinated, or misinterpreted data—we continuously harden our system against real-world failures.