Comparing Cresta and Level AI? Both are Agent Assist & Copilots and QA & Conversation Analytics tools in the directory, which is why buyers put them on the same shortlist. Below is a side-by-side look at how they price, what they integrate with, and when each is the better fit, so you can pick on the facts rather than either vendor's own sales page.
| Attribute | Cresta | Level AI |
|---|---|---|
| Pricing | Paid · Custom | Paid · Custom |
| Founded | 2017 | 2019 |
| Categories | Agent Assist & Copilots QA & Conversation Analytics Voice & Phone AI | Agent Assist & Copilots QA & Conversation Analytics |
| Integrations | Salesforce Five9 Genesys Amazon Connect NICE Avaya | Genesys NICE CXone Five9 Talkdesk Salesforce Zendesk |
Cresta started from a simple observation: in every contact center, a handful of agents dramatically outperform the rest, and everything they do differently is sitting in the call recordings. Founded in 2017 by Zayd Enam, Tim Shi, and Sebastian Thrun, the Stanford professor behind Google X and Udacity, Cresta mines those conversations to learn what the best performers do, then coaches every agent in real time: suggested responses, knowledge, and guidance appearing on screen during live calls and chats.
That real-time layer is still the heart of the product, but the platform now spans the full loop. Conversation intelligence gives leaders visibility into every interaction, automated quality management replaces sampled QA scorecards, a training simulator lets agents rehearse against AI customers, and autonomous virtual agents take the high-volume calls that never needed a human. It plugs into the major contact-center stacks, including Five9, Genesys, Amazon Connect, NICE, and Avaya, so it layers onto what you run rather than replacing it.
Cresta sells to serious operations: United Airlines, Alaska Airlines, Cox Communications, Marriott, and Brinks Home are named customers, and investors including Andreessen Horowitz, Sequoia, and Greylock have backed it to the tune of roughly $276 million, most recently a $125 million Series D in late 2024 that valued the company around $1.6 billion. Pricing is enterprise and quote-based, with no public numbers.
Cresta is the pick when your strategy is making human agents better rather than replacing them, especially in revenue-bearing conversations like sales and retention where a slightly better sentence is worth real money. If you want humans out of the loop entirely, look at the autonomous-agent specialists; if you want your hundred agents performing like your best ten, Cresta was built for exactly that.
Read the full Cresta listing → · See Cresta alternatives →
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.
Read the full Level AI listing → · See Level AI alternatives →
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