Healthcare’s Personalization Engine
Unlock the future of healthcare communication with Lirio.
Our Approach: Precision Nudging®
Precision Nudging is the core of our personalization engine and combines behavioral science and AI to activate and engage consumers.
Through this approach, Lirio creates and deploys interventions tailored to each person – with the right content, at the right time, and via the right channel – to overcome specific barriers to action on their unique health journeys.
Using Precision Nudging, Lirio equips you with behavioral insights about the individuals in your population to inform engagement strategies that fuel better health outcomes, reduce the total cost of care, and realize growth opportunities for your organization.
Introducing the World’s First Large Behavior Model for Healthcare
Lirio’s Personalization Engine is powered by our Large Behavior Model (LBM).
An LBM is the pioneering bridge between behavioral science and AI, with a singular mission — significantly enhance health outcomes through tailored recommendations and communications.
It informs the creation of a highly individualized representation that captures a person’s healthcare behaviors, motivations, and decision-making processes – which our Personalization Engine then uses to deliver tailored health interventions for each individual in your population.
The promise of this technology is that it automates personalization at enterprise scale.
The Lirio Large Behavior Model helps you realize a future where every person is empowered and experiences better health outcomes.
Core Capabilities
Lirio’s Personalization Engine is designed to address four continuous elements required for moving health consumers toward target behaviors and actions.
All of this occurs within a HITRUST-certified and SOC II Type 2-compliant framework to ensure your consumer data remains secure throughout.
We offer flexible deployment options and integrations, layering into your existing systems so you can maximize the value of your tech investments.
Lirio parses and integrates health journey, social context, engagement, and outcomes data from numerous sources to create a comprehensive understanding of the consumer as the basis for hyper-personalization, determining eligibility for each intervention.
Based on all eligible actions, Lirio’s technology identifies which is most important and how to optimize the likelihood of behavior change. Behavioral interventions are then leveraged to drive that health action, personalized with the right content, timing, and delivery channel for each individual.
Lirio’s behavioral reinforcement learning agents continuously learn from consumer interactions and automatically adjust interventions based on feedback data and reward signals until desired health outcomes are achieved, further enriching understanding of the consumer.
Lirio applies a constant stream of progressively smarter personalization to future interventions to drive continuous behavior change and support the consumer’s ongoing health journey. The result is better outcomes for the individual and a healthier population overall.
Core Features
The following core features of Lirio’s personalization engine work together to help healthcare organizations shift from transactional interactions to a relational approach with consumers.
Libraries of pre-built behavioral interventions designed to overcome barriers to health actions
Language translation and adaptation to ensure interventions are culturally appropriate and tonally accurate
Intervention delivery through a range of channels, including email, text, push notifications, and chatbots
Automatic deployment of behavioral interventions based on intelligent identification of the next best action
Client- and program-specific dashboards that highlight progress toward population and individual health outcome goals
Exclusive behavioral profiles and in-depth primary data enable one-to-one personalization and forecasting
Integration with your data infrastructure, engagement channels, and workflows
Cloud-native deployment in your environment of choice