Comparing Cresta and Observe.AI? Both are Agent Assist & Copilots, QA & Conversation Analytics and Voice & Phone AI 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 | Observe.AI |
|---|---|---|
| Pricing | Paid · Custom | Paid · Custom |
| Founded | 2017 | 2017 |
| Categories | Agent Assist & Copilots QA & Conversation Analytics Voice & Phone AI | Agent Assist & Copilots QA & Conversation Analytics Voice & Phone AI |
| Integrations | Salesforce Five9 Genesys Amazon Connect NICE Avaya | Amazon Connect Avaya 8x8 Aircall Jira BambooHR |
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 →
Observe.AI made its name by fixing quality assurance, the least loved job in the contact center. Instead of a QA team sampling two percent of calls and arguing about scores, it transcribes and analyzes one hundred percent of interactions, scores them automatically against your rubrics, flags compliance risks, and turns the results into coaching. For support leaders it answers the questions that sampling never could: why are customers calling, which behaviors actually move CSAT, and which agents need help this week rather than at quarter end.
Founded in 2017 by Swapnil Jain and headquartered in Redwood City, the company raised a $125 million Series C led by SoftBank Vision Fund 2 in 2022, with Zoom as a strategic investor, and serves names like DoorDash, SoFi, Accolade, and Asurion. Like most of the conversation-intelligence category it has pushed aggressively into agents themselves: its VoiceAI agents now automate routine calls end to end, real-time assist guides live agents mid-conversation, and an Agent Harness handles the unglamorous work of testing and versioning AI agents before they meet customers.
The platform advertises more than 250 integrations across contact-center, CRM, and workforce systems, and pricing is custom, scoped to seat counts and interaction volume, with nothing published.
Observe.AI fits operations large enough that measuring conversations is a full-time problem: if you have dozens of agents or more and your QA process is a spreadsheet and good intentions, full-coverage automated scoring changes how you manage. Teams that just want a bot to deflect tickets have simpler options; teams that want to understand and improve every conversation, human or AI, should shortlist it.
Read the full Observe.AI listing → · See Observe.AI alternatives →
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