Artificial Intelligence

Organized for Intelligence: Re-architect member data and content systems to support scalable AI training and deployment. This foundation enables advanced personalization, predictive insights, and next-gen engagement strategies.

CDP-Enabled Personalization: Identify and prioritize critical member data assets, then implement off-the-shelf Customer Data Platforms (CDPs) to streamline personalization, analytics, and omnichannel coordination.

Visionary Member Interaction Models: Define the AI-enabled member engagement model of tomorrow. Create a strategic blueprint that aligns with corporate goals and AI trends-setting the stage for transformative experiences and loyalty-building innovation.

Vision Meets Execution: Bridge corporate strategy with emerging AI capabilities. This use case focuses on aligning leadership vision with practical, scalable AI initiatives-speeding adoption while managing cost and risk.

Personalized Use Cases: Engagys partners with you to pinpoint the most impactful AI use cases for your member engagement-related opportunities, ensuring alignment with your organizational goals and maximizing financial impact.

From Hypothesis to Precision Strategy: Replace assumption-based strategies with real-time, AI-supported decision-making that evaluates unlimited variables to drive more accurate, unbiased outcomes.

Two-Way Communication at Scale: Use NLP and rules-based AI to automate bidirectional member communications via text and email-enabling more responsive, asynchronous interactions. A low to medium-risk use case with scalable third-party and in-house options.

GenAI-Driven Messaging: Use generative AI to tailor and optimize outbound communication materials for higher engagement and action rates. For example, Engagys’ LLM tool incorporates healthcare-specific engagement strategies and behavioral science techniques to craft personalized, impactful messages. The tool is a Retrieval Augmented Generation (RAG) solution that works as a plug-in to available LLMs – adding decades of practical healthcare consumer engagement experience to otherwise vanilla content.

Behavior-Driven Grouping: Use AI to create dynamic, scalable segments based on real-time behavioral data rather than static demographics - enabling more relevant, effective interventions.

Digital Touchpoints that Build Trust: Transform web and mobile experiences into responsive, intuitive tools that deepen member relationships.

Infinite Content Combinations: Leverage GenAI to generate personalized, action-specific content by assembling modular fragments - maximizing resonance and minimizing production cost.

Always-On Optimization: Use AI to measure engagement and outcomes at the individual level, enabling continuous learning, iteration, and performance improvement in real time - not just post-campaign.

Precision Engagement: Deliver AI-curated next steps tailored to each member’s health journey, increasing relevance and outcomes. Start with manual prioritization at the use case level (crawl), evaluating all member touchpoints using an agreed-upon framework. Progress to automated outbound prioritization at the communication level (walk) using a Customer Data Platform (CDP) to manage cohort-level journeys with holistic governance. Ultimately reach real-time orchestration (run) where AI triggers seamless, multi-channel communications based on individual behavior and continuously learns to optimize outreach effectiveness.

One-to-One Engagement Flows: Replace fixed marketing journeys with AI-orchestrated, adaptive engagement paths that respond to individual behaviors, preferences, and context in real time.

Total Data Integration for Hyper-Personalization: Pull, organize, review, and analyze all member interactions and data - across call center conversations, portal chatbot exchanges, health records, demographics, behaviors, pharmacy interactions, and provider engagements to generate a truly unified, 360° view. This enables predictive, contextual, and hyper-personalized experiences that adapt in real time to each member’s unique needs, preferences, and health journey.

AI-Guided Call Interactions: Apply GenAI and rules-based AI to observe agent-member dialogues in real time and suggest personalized scripting-enhancing resolution rates and call outcomes. Low to medium-risk with customizable, vendor-supported options.

Smarter Service with Contextual Help: Empower agents with AI-assisted access to relevant knowledge in the moment-improving resolution time and satisfaction.

Real-Time Agent Guidance: Analyze live conversations to coach call center agents on tone, timing, and messaging - boosting effectiveness and consistency.

Efficient Post-Call Processing: Use GenAI to transcribe conversations, summarize key points, and capture next steps-cutting down on post-call work and increasing throughput. A low-risk use case supported by a variety of off-the-shelf tools.

Automated Inquiry Resolution: Deploy a rules-based NLP chatbot in member portals to manage high-volume service questions, reducing call center load. This use case delivers strong ROI with a low to medium-risk profile and proven vendor solutions.

Automated Call Summaries: Leverage AI to transcribe and summarize call center interactions in real time, streamlining documentation and freeing agents to focus on member care.

Next-Gen Predictive Modeling: Enhance or replace aging predictive models with more accurate, AI-powered insights that anticipate member needs.

Personal Data, Personalized Care: Integrate AI with in-home devices to make individual health data more actionable and accessible for proactive care.

Cross-Condition Predictive Models: Use AI to understand interconnected conditions and deliver truly holistic care insights.

Real-Time Dietary AI: Detect and respond to food-related triggers using AI, enabling timely interventions for chronic condition management.

Connected Care Teams: Enable AI-enhanced coordination across multiple providers and the members’ health plan to reduce duplication and improve continuity of care.

Cost-Effective, Personalized Treatments: Recommend lower-cost treatment alternatives customized to a member’s data profile and medical history.

Navigating the dynamic AI vendor landscape can be daunting. Engagys conducts comprehensive assessments to cut through the noise and identify which vendors are best suited for delivering tailored solutions that meet your specific needs.

Engagys conducts a comprehensive assessment of your current AI-related technologies, tools, and infrastructure to identify gaps between your organization's existing capabilities and emerging AI opportunities. This includes evaluating data readiness, platform scalability, integration points, and current vendor solutions. The goal is to highlight what’s missing, what’s underutilized, and where investment will yield the greatest impact - enabling you to prioritize high-value AI initiatives and future-proof your technology stack.

From initial deployment to ongoing support, Engagys collaborates closely with your organization and AI vendors to streamline implementation processes, ensuring smooth integration and accelerated results.