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NEW REPORT: Q&A with Mike Gualtieri, VP Principal Analyst at Forrester

Intelligent Engagement
Business Goal Optimized AI
Real-Time Learning with Business Observability

Business Observability

Measure the business impact of AI across the enterprise

Data Driven Decisions

Run Simulations, Track and Monitor Outcomes and Refine Results in Real-time

Business Goal-Driven AI

Define Goals

The CognitiveScale Cortex AI Platform clearly defines business objectives using observable data-driven KPIs from connected data, models and actions

Target Cohorts

Defined subsets of populations for multiple "entities" (customer, client, patient, member, agent, etc) based on Profile-of-One

Create Missions

Goal-driven AI-Powered Campaigns have multiple Missions with many interventions that drive value

Run Simulations

Enable reinforcement learning by running simulated Missions that accelerate speed to value

Refine

Refine goals, cohorts, mission plans and interventions based on continuous learning and feedback

Goal-Driven AI Solutions

Empowers Businesses to Make Data-driven Decisions that Result in the Best Possible Outcomes

Run Simulations, Track and Simulate Outcomes and Refine Results in Real-time

  • Cortex platform allows users to clearly define business objectives using observable data-driven KPIs from connected data, models and actions
  • Enables business users and subject matter experts to generate AI applications that drive value by continuously measuring and optimizing to stated business goals
  • Customer missions achieve a goal state using interventions, or recommendations, to generate AI-powered models that optimize to achieve a desired goal
  • An intelligent automation program connects groups of cognitive interventions with bots (e.g., RPA, cognitive and chat) and runs intervention simulations using simulated or synthetic datasets prior to deployment to production
  • Customer profiles are updated in real-time and the system "learns" so the next deployment of interventions is incrementally more effective
  • Select the best implementation strategies using feedback from intervention simulations to link AI-powered applications to business goals

Goal-Driven artificial Intelligence

Example Use Case

Example use case of goal-driven AI
Example use case of goal-driven AI

Business Goal Optimized AI Campaign Components & Personas

Business Goal Optimized AI Campaign Components & Personas

 

We Bridge the Gap

Between AI Technologies and Outcomes

There is a large gap between AI technology—the data science, data engineering, and machine learning (ML) software and infrastructure—and business outcomes—the value derived from AI-powered applications and decision intelligence.

We create synergy across the entire AI lifecycle—from DataOps and ModelOps through DevOps, management, and monitoring—and drive value and business outcomes with trusted decision intelligence, customer-centric, AI-powered personalization, insights, and the mitigation of risk and bias.

We engineer this by Connecting your data and models, Orchestrating business logic into your apps, Personalizing recommendations with evidence and insights, and Continuous Learning through campaigns and missions with goal-driven AI that improve model and application performance.

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Q&A with Mike Gualtieri, VP Principal Analyst at Forrester
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