Precision intelligence for radiation oncology
Make cross-workflow variation visible. Prioritize review. Strengthen clinical consistency.
A read only, explainable intelligence layer across contouring, planning, and workflow signals.
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The Problem
The gap is not inside individual reviews
Radiotherapy workflows are rigorous and protocol-driven. Quality assurance is embedded at multiple checkpoints, and individual reviewers bring deep clinical expertise to each case they evaluate. The systems are not broken in isolation.
But contouring, planning, and QA signals are rarely evaluated together. Each domain maintains its own review cadence, its own documentation, and its own criteria for escalation. The connections between them remain implicit visible only in retrospect, if at all.
What remains hidden
Hidden variation
Cross-workflow patterns that no single review surfaces
Uneven review effort
High-complexity cases not always prioritized systematically
Limited visibility
No unified view across contouring, planning, and QA
The Insight
Variation often spans across workflows
Individual review processes catch errors within their domain. What they do not capture is the compounding effect of variation across domains, where contour decisions influence planning trade offs, and planning trade offs drive QA rework.
These relationships exist in every high-volume radiotherapy program. They are not random. They are systematic, and they are rarely connected in a way that makes them actionable before review effort is already expended.
Solution
A read-first intelligence layer across radiotherapy workflows
OncoREI does not sit inside a single system. It operates across the signals that contouring, planning, and workflow environments already generate, aligning them, contextualizing them against comparable cases, and surfacing structured deviation for expert review.
Aligns signals
Connects data across contouring, planning, and QA systems without modifying them
Compares to cohorts
Cases are evaluated relative to similar cases treated under similar protocols
Surfaces deviation
Multi-signal patterns drive prioritization, not single-point flags
Prioritizes review
Directs expert attention to cases where cross-workflow signals warrant it most

Not prediction. Not automation. Prioritized, explainable insight.
How It Works
Four principles. One coherent layer.
OncoREI is designed around clinical workflow integrity. Every component is intended to support the reviewer, not redirect clinical judgment or introduce opaque automation.
Signal Alignment
Contour, plan, and workflow signals are read and combined into a unified case-level representation, preserving source fidelity at every step.
Cohort Comparison
Each case is evaluated relative to structurally similar cases, same site, similar fractionation, comparable anatomy, to contextualize deviation within a meaningful reference frame.
Deviation Detection
Multi-signal alignment drives prioritization. Cases surface when the convergence of signals warrants expert attention.
Explainability
Every signal is visible and interpretable. The reviewer sees what the system sees. There are no black-box scores, no opaque rankings, no unexplained flags.
Product
From signal to structured review
OncoREI is not a dashboard layer placed on top of existing systems. It is a structured intelligence flow, that moves from raw signal capture through contextual analysis to review-ready output, without disrupting the clinical environments it connects.
The system does not determine correctness. It helps the right cases get the right attention, at the right point in the review cycle, with the signals that support clinical reasoning already assembled.
Value
Designed for high volume and high rigor environments
OncoREI is built for programs where clinical throughput is high, case complexity is significant, and the cost of undetected cross-workflow variation is measurable. The intelligence layer adapts to the program, not the other way around.
For Hospital Programs
Regional cancer centers and high-volume radiotherapy departments benefit from structured prioritization that reduces hidden workflow burden, surfacing cases that warrant senior review before inefficiencies compound.
For Academic Centers
Academic and research-affiliated programs gain a consistent framework for cross-case comparison, supporting structured learning, resident oversight, and protocol consistency across complex treatment sites.
For Clinical Teams
Radiation oncologists and medical physicists receive clearer, coordinated signals reducing the interpretive burden of cross-system review and enabling more targeted, explainable escalation decisions.
Safety
Clinically careful by design
Design constraints: not features
The boundaries of OncoREI are not implementation choices. They are core design commitments, maintained regardless of deployment context or institutional configuration.
01
Read only
No write access to clinical systems. No modification of records, plans, or contours.
02
Retrospective first
All analysis is retrospective. The system does not intervene in active treatment delivery.
03
No clinical automation
OncoREI generates no clinical decisions. Prioritization is a prompt for human review, not a substitute for it.
04
Explainable at every step
Signal weights, cohort references, and deviation logic are visible to the reviewing clinician at all times.
Supports, does not replace, clinical judgment
The clinical team retains full authority over every case. OncoREI surfaces structured context, it does not interpret that context, assign clinical significance, or recommend action. The reviewer determines whether a flagged case warrants intervention.
This is not a regulatory position or a liability disclaimer. It is an architectural commitment embedded in how the system reads, processes, and presents information. The intelligence layer is designed to be invisible to the patient pathway and transparent to the clinical reviewer.

OncoREI is a concept prototype. It is not a cleared clinical decision support system and is not intended for use in active clinical decision-making.
Pilot
Start with a controlled retrospective pilot
OncoREI is designed to be validated before it is relied upon. A structured retrospective pilot allows your team to evaluate signal alignment, cohort logic, and prioritization output against cases where expert ground truth is already established.
Limited Dataset
Pilot engagements use a defined, bounded case set — typically 3–6 months of retrospective data — to establish baseline signal fidelity without system-wide deployment.
High-Complexity Sites
Head and neck and lung cases are prioritized for initial validation, where cross-workflow variation is clinically significant and expert reviewers can assess alignment with confidence.
Expert Validation
Prioritization output is reviewed alongside institution-based expert assessment — validating whether the system surfaces the cases experienced reviewers would have flagged.
No Workflow Disruption
The pilot operates entirely in a read-only, offline analytical environment. Existing clinical systems, review processes, and treatment delivery are unaffected.
Contact
Explore whether this fits your environment
OncoREI is an early-stage concept. We are engaged in structured conversations with radiation oncology programs, medical physics leadership, and health system administrators who are evaluating cross-workflow intelligence as a clinical quality priority.
If your program operates at high volume, treats complex sites, and maintains a rigorous internal review culture we would welcome a direct, substantive discussion about what a retrospective pilot could reveal in your environment.
Radiation oncology intelligence. Cross-workflow visibility. Explainable prioritization.
contact@oncorei.ai
Disclosure
Concept prototype, not a clinical decision system.
OncoREI.ai is in early-stage development. This website describes a conceptual framework and does not represent a cleared, approved, or commercially available medical device or clinical decision support product. All capabilities described are subject to validation, regulatory review, and institutional assessment prior to any clinical deployment.