Agent Assist & Copilots Contact Center & CCaaS QA & Conversation Analytics
AI-first quality assurance and analytics for customer service teams.
Level AI is what happens when someone who helped build Amazon's Alexa turns the same technology on the contact center. Founder Ashish Nagar worked on the Alexa Prize conversational AI effort before starting Level AI in 2019, and the product's core bet is that quality assurance should be about meaning, not keywords. Its semantic engine scores every conversation against your rubrics by understanding intent, so an agent who solved the problem politely but never said the magic phrase still scores well, and one who recited the script while losing the customer does not.
Automated QA is the anchor, and around it the platform builds the full intelligence loop: real-time agent assist that surfaces answers from your knowledge sources during live conversations, voice-of-customer analytics that tell leaders what is driving contacts and sentiment, agent screen recording for the full picture, and AI virtual agents for handling routine interactions outright. It integrates with the usual suspects, including Genesys, NICE CXone, Five9, Talkdesk, Salesforce, and Zendesk.
The company, based in Mountain View, has raised about $73 million, most recently a $39.4 million Series C led by Adams Street Partners, and counts Vistaprint, Purple, Extra Space Storage, and Smartsheet among its customers. Pricing is quote-based with nothing public, typical for the category.
Level AI competes most directly with Observe.AI and the QA suites inside bigger platforms, and the honest differentiator is its semantic scoring and analytics depth. Shortlist it if your QA program has outgrown checklists and you want conversation data treated as a source of insight rather than a compliance chore, especially if you run a mid-size to large team on one of the contact-center platforms it plugs into.
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Updated July 2026
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