Why choose Level AI over Qualtrics?
Qualtrics revolutionized feedback management, but the CX landscape has evolved. Today’s leaders need more than static surveys — they need real-time visibility into quality, performance, and customer emotion across every interaction. That’s why they’re moving to Level AI.
Why Levelai
Beyond traditional AI: how LevelAI outperforms Qualtrics
Unified CX intelligence platform vs survey-led feedback management tool
iCSAT on 100% of conversations vs limited, sample-based survey responses
Actionable, explainable insights in real time vs delayed, post-event reporting
Unified CX intelligence, not survey-centric feedback
Level AI captures, analyzes, and interprets 100 % of real customer interactions (voice, chat, email) in real time.
Qualtrics depends on post-interaction surveys and form-based feedback, offering partial CX visibility and slower insight loops.
Explainable QA that builds trust
Unlike legacy bots that output scores, Level AI’s QA-GPT explains every evaluation with timestamps, reasoning, and evidence. Teams gain context, accuracy, and trust at scale.
Real-time iCSAT and CX visibility
While traditional systems depend on post-call surveys, Level AI’s iCSAT measures satisfaction and sentiment across 100% of conversations — giving leaders a live, data-backed view of customer experience health.
Instant CX feedback. Zero surveys required.
Real-time intelligence, not after-the-fact reporting
Qualtrics measures how customers feel. Level AI lets you act, optimize, and improve every conversation through unified QA, VoC, coaching, and automation
Comparison
LevelAI vs. Qualtrics: A closer look
Feature | LevelAI | Qualtrics |
|---|---|---|
Platform scope | ✓ - Unified CX stack covering QA, VoC, Coaching, Analytics, Agent Assist, Virtual Agent | X - Experience management platform: feedback, journey analytics, predictive insight |
Quality / Auto-QA | ✓ - Explainable QA-GPT: automated scoring with reasoning, evidence, timestamps | X - Quality modules are tied to survey and feedback tagging; no full conversational QA layer public |
Voice of the Customer (VoC) | ✓ - Supervised + unsupervised models surface themes, trends, sentiment automatically | X - Uses text analytics, sentiment, predictive feedback models across survey & feedback sources |
Inferred CSAT (iCSAT) | ✓ - iCSAT applied to 100% of conversations — no survey dependency | X - Predictive models and feedback-based CSAT, but less continuous inference across every interaction |
Virtual agent / AI agent | ✓ - Native Voice + Chat Virtual Agents integrated with QA/VoC | X - Focus is on feedback, analytics, and experience measurement — AI agents are not core |
Agent assist & coaching | ✓ - Real-time Agent Assist + coaching tied to QA & VoC feedback | X - Coaching and feedback workflows based on survey and feedback outputs; less live assist |
Screen recording | ✓ - Synced audio + agent desktop recording for quick context and QA validation | X - Separate recording / playback systems; not layered with QA interface |
Join us in turning customer conversations into insights that actually drive change
Compare
