Level AI

Level AI helps CX leaders free up agents, automate 100% of QA, and resolve 70%+ of tickets with AI agents. All it takes is a 30-min discovery call to see how leading teams are transforming CX. 🎁 And as a thank-you for your time, you’ll unlock a $300 gift — Airbnb, Amazon, or Apple Watch.

Yesterday, we took to the streets of Microsoft Ignite in San Francisco with an all-too-familiar tune. If you heard it, you knew why. Thanks to everyone who jammed with us and got a firsthand look at better CX 🎶

Can AI accurately detect mental health risks before humans do? Mental health providers face a critical challenge: identifying when patients are at risk before it's too late. Humans alone cannot instantly review every patient interaction or easily notice important warning signs. One organization uses an AI-driven solution to listen closely to patient conversations, automatically identifying language signaling suicidal thoughts. When AI detects these critical moments, it alerts caregivers, enabling actions that may save someone's life. Integrating artificial intelligence into mental health workflows can create quicker, smarter, and more dependable crisis responses compared to manual methods. With Level AI's help, mental health professionals can concentrate their time and efforts precisely where they are needed most. We want your opinion: Do you think AI can effectively assist in mental health crises?

You don't have to be the smartest person in the room, but you do need to be the fastest learner when technology shifts every few months. That's how Paul Jarman, Executive Chairman at Paul Gigg and Former CEO at NiCE, survived 25 years of industry transformation, from premise to cloud, single-tenant to multi-tenant, traditional analytics to AI automation. His approach is divided into four core elements: 1. Prioritize curiosity over current intelligence. 2. Develop "micro-understanding" without micromanaging. 3. Embrace being wrong as a competitive advantage. 4. Focus on iteration speed rather than perfect starting positions. Current expertise becomes obsolete quickly, but learning velocity determines long-term career progression. #CustomerExperience #AIStrategy #ProductManagement #TechLeadership #FutureOfAI #DigitalTransformation #CXLeadership #ServiceStrategy #GenerativeAI #TechROI

How AI can deliver ROI in contact centers beyond "autoQA" and "chatbots"? Contact center leaders often ask us this question. Here are two micro case studies showcasing how Level AI has provided immediate and measurable returns: Case Study #1: Uncovering Hidden Conversion Blockers 🛋️ An online furniture retailer used our VOC feature to analyze customer calls. The insight revealed that customers abandoned carts when purchasing items needing multiple shipments with white glove installation. The issue was the grayed-out white glove option during checkout. After modifying the checkout process, there was a reduction in cart abandonment and increased conversion rates. Case Study #2: Detecting Broken Payment Flows 💳 After revamping their checkout process, an e-commerce client experienced a spike in customer service calls related to a digital wallet payment method. Our analysis found a broken link to the wallet, affecting about 10% of customers. The company fixed the issue promptly, reducing late-stage funnel leakage. Bottom Line: 🔍 Level AI monitors all conversations in real-time, addressing concerns and emerging problems swiftly. Unlike manual processes, AI can detect issues proactively, saving time and improving customer experiences. Curious about uncovering hidden issues in customer conversations? Let's chat. #ContactCenterAI #ConversationIntelligence #ConversationalAI #generativeAI #CustomerExperience #ROI #ConversionOptimization #DigitalExperience

Your call is being recorded for quality assurance purposes :) <1% of these calls are being evaluated by the average enterprise. What if the other 99% could be leveraged? Unstructured customer service data is a treasure trove of customer insights, only for the bulk of this data to not be recognized. Using Agentic AI one can now mine these conversations in an unprecedented way. A lot of focus of Generative AI systems has been on automation, the Intelligence use cases of mining this untapped data is a much more low hanging and high ROI use case. Thoughts?