Identify automation opportunities and streamline work.
Realize fast results with in-depth CX insights from purpose-built AI. Optimize agent tasks, increase digital resolutions, reduce customer effort, and decrease costs by building bots that reflect top agent workflows.
“Simply put, our self-service needed to get better, and Enlighten XO got us on the path to success.”
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Eliminate guesswork.
Powered by purpose-built AI for CX, Enlighten XO combines the largest dataset of historical conversational data with businesses’ voice and text interactions to prioritize top automation opportunities by ROI and eliminate guesswork. Data-driven self-service identifies and understands customer intents and utterances, and mirrors top-performing agents to build effective tasks and workflows across all channels.
Enlighten XO leverages the largest CX dataset of conversational interactions to understand customer intents using advanced AI. It analyzes businesses’ existing voice and text conversations to identify top automation opportunities, tasks agents complete to resolve inquiries and map the optimal workflows.
By analyzing top-performing agents' behaviors and workflows, Enlighten XO designs self-service to mirror top-performing agents, increasing digital resolutions and improving customer experience.
By continuously learning from all voice and text conversations, Enlighten XO’s purpose-built AI for self-service discovers customer intents, utterances, agent workflows, and the top ROI opportunities so businesses can quickly build self-service that resolves more interactions in digital channels.
Enlighten XO's key differentiators in the conversational AI space are its ability to use AI to learn from conversational data across all channels combined with the largest multi-industry collection of out-of-the-box intents purpose-built for CX, prioritization of top automation opportunities by ROI, and codeless integration of intents, utterances and optimal agent workflows into intelligent virtual agent (IVA) platforms like Enlighten Autopilot.
Ingest timeframes are defined in the DEF workflow and set at deployment time. These timeframes can be as often as is desired to meet the customer’s needs, within the limits supported by the data source(s).
XO is bot-agnostic, meaning it can inject intelligence to make ANY bot smart, whether it’s NICE’s, or your own. The time-to-value can be greatly accelerated when combined with codeless integration to NICE’s Enlighten Autopilot.
Enlighten Autopilot is purpose-built AI for consumers. Provide personalization at scale for increased customer loyalty, delivering seamless experiences via digital journeys or AI-designed virtual agents. Provide consumers with customized self-service when and where they need it with trusted company knowledge to align every response with brand and business goals.
Basic analyst skills
Bot Building skills and IVA solution (e.g., Autopilot). Enlighten XO provides data to help build better bots, fast.
Start with data, not a workshop
Take the guesswork out of self-service development with conversational data from voice and text interactions.
Automate effective resolution faster
Prioritize the most impactful opportunities and develop new self-service capabilities.
Increase self-service success
Gain valuable insights into customers’ evolving needs and take a data-driven approach to power digital CX.
Bot-agnostic
Inject intelligence to make ANY bot smart, whether it’s NICE’s, or your own.
Leverage customer language
Uncover training phrases based on real-life language for specific insights into each customer’s needs to accelerate self-service time-to-value.
Optimize agent tasks
Train your bots to resolve intents the same way as your best agents so you resolve more interactions in self-service.
Data-driven self-service
Eliminate guesswork and turn to data for truly intelligent virtual agents that reduce customer effort.
Requires familiarity with contact center metrics such as duration, sentiment, interaction volume, etc.
Requires the ability to use filters of various types to create Target Media Sets to identify the interactions of interest on which to run an Enlighten XO project.
