AI & Analytics

The Platform That Puts Real-Time Transplant Data at the Center of Every Decision

Afflo is more than software. It is the connective layer between your clinical workflows, your institution’s models, and the real-time transactional data that no other platform can provide.


Why afflo is different:

AI Needs the Right Data. Afflo Has It — In Real Time.

Most AI tools in healthcare are built on static datasets and historical exports. Afflo is different. Because Afflo is the operational core of your transplant program, every clinical event — a new referral, a lab result, an organ offer, an acceptance decision — is captured the moment it happens.

That real-time, end-to-end transactional data is what AI models need to deliver meaningful predictions and insights. Afflo provides the platform to plug in, train, and run those models where they matter most: at the point of clinical decision-making.

Afflo functions as the AI integration layer for transplant. Whether you are deploying Afflo’s own validated models or connecting your transplant center’s proprietary research models, the platform provides the secure data pipelines, inference APIs, and clinical UI components needed to bring those models to life — in the workflow, at the right moment.

No other transplant platform can offer this. The granularity and real-time nature of Afflo’s data — spanning donor evaluation, waitlist status, HLA matching, organ logistics, and post-transplant outcomes — is simply not available elsewhere.

01

Real-Time

Transactional data across every clinical touchpoint — referral through outcomes

02

End-to-End

The only platform covering the complete transplant lifecycle — donor to follow-up

03

Open

Connect Afflo’s AI modules or integrate your transplant center’s own research models

Intelligence Embedded Where It Matters

Afflo’s AI is not a dashboard bolted onto a separate system. It is embedded within the clinical workflows your teams already use, surfacing the right information at exactly the right moment — without adding steps or friction.

Intelligent Referral Intake & Document Processing

Incoming referral packets — faxes, PDFs, scanned forms, consult notes, lab results — are automatically ingested, parsed, and converted into structured clinical records. Coordinators review and validate rather than transcribe, reducing intake time significantly and cutting the risk of missed eligibility criteria. The AI understands transplant-specific clinical language and extracts key demographic, diagnostic, and immunologic data into Afflo’s standardized fields — ready for evaluation from day one.

Waitlist Intelligence & Risk Monitoring

Afflo continuously monitors the status of every patient on your waitlist — tracking testing intervals, expiring workups, psychosocial requirements, and eligibility changes. AI-generated alerts surface patients at risk of suspension or removal before problems occur, keeping coordinators proactive rather than reactive.

Organ Offer Decision Support

When a donor organ offer arrives, the clock starts. Afflo’s AI analyzes donor and recipient data in real time, surfacing compatibility considerations, relative risk factors, and any anomalies or missing data that a time-pressured team might otherwise overlook. Side-by-side panels within the offer workflow display AI-generated predictions alongside the clinical data your surgeons and coordinators already review — designed to support faster, more confident decisions around the clock.

Integrated Logistics & Coordination Intelligence

Organ viability is time-critical. Afflo incorporates transport timelines, routing variables, ischemic time estimates, and procedure scheduling into offer evaluation — ensuring logistics are never the reason a decision goes wrong.

Predictive Decision Analytics

Afflo’s data platform supports two complementary predictive models that help clinical teams make better offer decisions: Expected graft survival — an estimate of patient and organ outcomes if this offer is accepted, based on donor and recipient characteristics. Time to next comparable offer — a prediction of how long a patient may wait if this offer is declined, helping teams weigh the trade-offs

Performance Insights & Utilization Analytics

Afflo’s data warehouse turns the full granularity of your program’s operational data into dashboards that reveal utilization patterns, equity metrics, allocation outcomes, and coordinator workload trends — giving leadership the visibility needed to improve continuously.

OPEN PLATFORM ARCHITECTURE

Bring Your Models. We Bring the Data.

Afflo is designed to be the integration platform for AI in transplant, not just the provider of it. Transplant centers and research teams that have built their own predictive models can connect them to Afflo through secure, standards-based APIs, running inference against live clinical data without manual data exports or re-entry.

What Afflo Provides

  • Real-time access to the full transactional data record — donor, waitlist, matching, offer, outcomes

  • Secure inference API framework for plugging in external models

  • Configurable UI panels to surface model outputs within existing clinical workflows

  • Audit-ready logging of AI-assisted decisions for compliance and review

  • Data warehouse and analytical layer for model training and validation

  • Policy simulation tools to test the impact of AI-informed changes on historical data

What Your Team Brings

  • Institution-specific predictive models trained on your program’s patient populations

  • Research models developed through academic or clinical partnerships

  • Jurisdiction-specific algorithms for allocation policy optimization

  • Specialty organ models (liver, kidney, heart, lung) adapted to local practice patterns

  • Validated models from published research, ready for deployment into clinical settings

The data problem in transplant AI is not a shortage of researchers or algorithms — it is a shortage of real-time, end-to-end operational data. Afflo solves that problem. When your model runs inside Afflo, it runs on the most complete, most current transplant data available.

CLINICAL USE CASES

Where AI Creates Impact in Transplant

Afflo’s AI capabilities are focused on the specific moments where evidence and speed combine to change patient outcomes. Each use case is validated against real-world transplant workflows and designed to support — not replace — clinical judgment.

01 Automated Referral Intake for Kidney & Liver Programs

Transplant coordinators at high-volume centers receive hundreds of referral packets annually in heterogeneous formats — faxes, scanned handwritten forms, partial attachments. Afflo’s document AI ingests and structures these into standardized records, reducing intake from approximately 3 hours per patient to under 1.5 hours while cutting transcription errors and accelerating time-to-evaluation.

02 Predicted Graft Survival at the Time of Offer

When a deceased-donor kidney or liver offer arrives, Afflo surfaces a predictive graft survival estimate computed from donor clinical characteristics (including KDRI and KDPI), recipient health status, compatibility factors, and logistics. This quantitative signal is presented alongside existing case data to support faster, more consistent acceptance decisions — especially during overnight shifts and high-volume periods.

03 Time-to-Next-Comparable-Offer Prediction

Declining an organ offer is often the right decision — but it is rarely made with full information about what comes next. Afflo’s predictive model estimates the expected wait time to an organ offer of equivalent or better quality, enabling surgeons and patients to weigh the real trade-offs. Research has demonstrated that older waitlisted candidates in particular may derive significant benefit from organs they might otherwise decline, and that this type of insight meaningfully reduces both unnecessary organ discards and overly conservative decisions.

04 Waitlist Mortality Risk & Patient Prioritization

AI-generated risk scores help coordinators and physicians identify patients at elevated risk of deterioration or mortality while waiting, enabling targeted clinical follow-up and priority review. Integrated with Afflo’s waitlist management workflows, these signals surface automatically within daily task queues — no separate reporting step required.

05 Policy Impact Simulation & Allocation Analytics

Afflo’s Policy Management Workbench allows transplant networks and oversight bodies to simulate proposed allocation rule changes against historical data before deployment. AI-assisted analysis surfaces the likely impact on organ utilization, equity metrics, and patient outcomes — enabling evidence-based policy decisions at a jurisdictional scale.

WHY IT WORKS

AI That Is Grounded in Real Transplant Operations

Data That No Export Can Replicate

Afflo captures every clinical event in real time — not as a nightly batch export, not as a manual database pull. When AI models run inside Afflo, they operate on the current state of every patient, every donor, and every offer. That currency is what makes predictions clinically meaningful.

Incremental Adoption, Not a Rip-and-Replace

Afflo’s modular architecture means AI capabilities can be added to your existing program without a full platform migration. Deploy a single capability today — document ingestion, offer analytics, or waitlist monitoring — and expand as your team builds confidence and appetite.

People Stay in the Workflow

Every AI feature in Afflo is designed to augment the clinician, not to replace them. Coordinators review and validate AI-extracted data. Surgeons receive predictive signals as one input among many. The AI handles the volume and complexity; the human makes the call.

Audit-Ready and Compliance-Aligned

Every AI-assisted decision is logged with full traceability. Afflo is designed to meet the rigorous transparency requirements of transplant oversight bodies, including support for equity reporting and allocation audits.

Purpose-Built for Transplant

Afflo’s AI was developed in close collaboration with transplant clinicians, coordinators, and investigators. Every model and interface was designed around the specific language, constraints, and urgency of transplant — not adapted from a general clinical AI toolkit.

A Framework That Grows

The inference infrastructure, API layer, and UI framework built to deliver today’s AI capabilities are designed to support tomorrow’s models — whether that means tissue matching, diagnostic imaging integration, or new predictive applications as transplant science evolves.

Ready to Connect Your Program to the Future of Transplant AI?

Whether you are looking to deploy Afflo’s validated AI modules or integrate your institution’s own models into a real-time clinical platform, we would like to show you what is possible.