
AI-powered Quality Management auto-scoring 100% of conversations against the customer-defined QA rubric — fitting contact-center operating models whose compliance posture, coaching cadence, or CX-improvement program requires full-coverage QA rather than statistical inference from sample-based manual review of 1–5% of calls.
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More from Level AI
AgentGPT delivers real-time agent assist grounded in the customer's knowledge base — surfacing relevant policies, procedures, and answers inside the conversation as it happens rather than after-the-fact coaching, fitting operating models whose AHT, FCR, and quality posture depends on agents having the right information at the moment of the call.
AI-powered insights and CX analytics across the full conversation corpus — surfacing emerging issues, root-cause patterns, agent coaching opportunities, and CX blind spots that sample-based QA misses, fitting operating models whose CX maturity has outgrown sample-QA and channel-specific reporting.
AI coaching and performance management workflows tied to QA scoring and conversation analytics — replacing the disconnected QA-rubric / coaching-spreadsheet / performance-review posture that most contact-center operating models default to.
Coverage across voice, chat, email, and digital channels under one platform — fitting contact-center operating models whose channel mix spans voice and digital and whose QA / coaching / analytics posture needs to be consistent across channels rather than running separate voice-QA and digital-QA programs.