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CORTEX AI ENGINEERING
Paving the Way to Client-centric AI

Articles
Friday, June 10, 2022

Cortex AI Engineering: Paving the Way to Client-centric AI

CognitiveScale’s Cortex AI Engineering platform is build on three pillars: AI Application Development (Composite AI), Personalization and Trust and Governance. As AI evolves from the MLOps era to the era of Client-centric AI, these foundational pillars become more important and impactful. It is important to understand each of these areas and how they impact the speed to production and value for AI applications, and components of the Cortex platform.

Client-centric AI

Pillar 1: AI Application Development or “Composition”

Cortex is a low-code collaborative developer platform for automating development and control of trusted AI applications. Cortex includes open, extensible building blocks convert any existing data (structured, unstructured) and any model (ML, non-ML). The Cortex AI Engineering platform includes:

  • Connect Any Data and Models: Cortex simplifies the integrations of customer data, models, rules and analytics from favored languages, model frameworks and providers and enterprise back-end systems
  • Orchestrate and Accelerate In-house AI Application Development: Cortex allows users to visually assemble and orchestrate open, extensible AI building blocks using a low-code, collaborative developer workbench that speeds up production of AI powered applications
  • Deliver Business Goal Optimized AI: Fabric Campaigns enable business users and subject matter experts (SMEs) to generate AI applications that drive value by continuously measuring and optimizing to stated business goals and objectives
  • AI Accelerators & Application Blueprints: Reusable and adaptable industry specific application blueprints allow AI developers to rapidly configure, train, deploy and evolve high-value AI powered processes

Connection, Data and Model Types

Pillar 2: AI-powered Personalization or “Personalization”

AI-powered Personalization relies on a cognitive data layer that infuses decision intelligence into customer acquisition, engagement and service. Cortex includes a key component called Profile of One that helps organizations build customer profiles that include data, models and rules engines that power AI solutions to deliver highly personalized, predictive and actionable insights.

Profile-of-One collects data from systems of record and engagement and uses it to derive inferences and next best actions for a given profile. This enables AI powered personalization at scale and provides a foundation for adding additional insights (risk scores, predictions, etc.). Cortex also enables rich customer profiles powered by AI that continuously learns, capturing data through the entire customer journey and across all touchpoints: email, web, social, service, demographics and more.

Cortex predictive insights

Typical Profile of One use cases:
  • Classification: Predict entities belonging to categories
    • Example: Call likelihood for an insurance claim
  • Similarity: Find similarities between entities
    • Example: Finding similar profit centers for a commercial customer
  • Segmentation: Identifying and grouping similar entities
    • Example: Members that are prone to being delinquent on a loan or medical bill
  • Forecasting & Simulation: Simulate “what if” scenarios using synthetic data
    • Example: Time series forecasting of new admissions for Covid-19 patients
  • Personalized Insights: Get insights and evidence based on learnings about a customer
    • Example: Detect agent fraud based on prior transactions and policy enrollments
  • Feature Store: Use Profile-of-One to power different ML model training and inferences
    • Example: Classification model for fraud, waste and abuse in medical claims
  • Temporal Analysis: Query for changes to a profile over time
    • Example: How customer behavior or characteristics (married vs. widowed) changed over time
AI-powered Personalization is common in several lines of business:
  • 1. Customer Acquisition
    • Boost lead quality & secure new customers
    • Drive more relevant, personalized shopping experiences
    • Present more personalized products and services (offer presentment)
    • Drive higher conversion rates (from leads to prospects, prospects to applicants, and customer conversion)
    • Lower abandonment rates
  • 2. Customer Engagement
    • Know the right message, channel & time to maximize outreach
    • Drive a contextual, multichannel experience
    • Move from reactive to proactive experiences
  • 3. Customer Service
    • Predict caller intent with agility
    • Prescribe resolutions proactively
    • Improve Service KPIs e.g. lower average handling time (AHT)

Pillar 3: AI Trust and Governance or “Responsible AI”

Trust in models and applications, responsible use, and governance are requirements for AI-powered Personalization. Cortex can generate a composite trust score, the AI Trust Index, that measures data and model risks related to performance, data quality, robustness, explainability, fairness, and compliance.

AI Trust

Cortex drives trust and governance in a number of key ways:
  • Effectiveness: In order to trust predictions made by AI, users must be able to measure effectiveness of the predictions in solving target business problems
  • Bias and Fairness: Ensure that data and models are representative of the real world and AI models are free of algorithmic biases
  • Explainability: Understand stakeholder concerns for decision interpretability and provide business process, algorithmic and operational transparency
  • Robustness: Provide the ability to detect and mitigate adversarial attacks while understanding how issues with data quality impact system performance
  • Data Quality: Ensure user visibility around data drifts, data poisoning, data validity and fit while certifying legal justifications to use and process the data
  • Compliance: Ensure systems operate within boundaries of local, national and industry regulation and are built and controlled in a compliant and auditable manner

Summary: AI Engineering will enable Client-centric AI

Client-centric AI will require AI Application Development that includes AI-powered Personalization as well as Trust & Governance. CognitiveScale’s Cortex AI Engineering platform is helping clients deliver robust AI roadmaps that include numerous Client-centric AI applications.

Contact Us to Learn More

Get in touch to get answers to these questions and learn more about how we can help your organization realize value from AI.

Email: sales@cognitivescale.com
Phone: 1-855-505-5001
www.cognitivescale.com

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