Comparing Loris and Observe.AI? Both are Contact Center & CCaaS 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 | Loris | Observe.AI |
|---|---|---|
| Pricing | Paid · Custom | Paid · Custom |
| Founded | 2018 | 2017 |
| Categories | Contact Center & CCaaS QA & Conversation Analytics | Agent Assist & Copilots Contact Center & CCaaS QA & Conversation Analytics Voice & Phone AI |
| Integrations | Zendesk Salesforce Kustomer Gladly LivePerson Twilio | Amazon Connect Avaya 8x8 Aircall Jira BambooHR |
Loris is a conversation intelligence platform that turns customer service interactions into structured data. It ingests voice calls, chats, and emails, then uses a mix of proprietary models and large language models to detect intent, sentiment, and quality signals across 100 percent of conversations rather than a sampled slice. That powers three jobs: insight into why customers contact you and how sentiment shifts, automated QA scoring of policy adherence and resolution, and analytics on AI agents, tracking containment, transfers, and abandonment so automation does not quietly degrade the experience.
Loris grew out of Crisis Text Line, the nonprofit text hotline, on the theory that empathetic language patterns learned there could improve commercial support. The New York company raised a $12 million Series A in April 2022 led by Bow Capital with ServiceNow Ventures, Floodgate, and Vertex participating, roughly $19 million total, under CEO Etie Hertz. Gartner named it a Cool Vendor, Harvard Business School wrote a case study on it, and pizza marketplace Slice credited it with a 36 percent drop in credits issued. In July 2025 Contentsquare agreed to acquire Loris, and the deal closed on October 23, 2025.
Loris never published pricing and still does not. Everything is quote based, and the product is now sold as the Conversation Intelligence module of the Contentsquare experience analytics platform, so expect an enterprise sales conversation rather than a credit card signup, likely alongside a broader Contentsquare pitch.
Choose Loris if you want conversation data connected to digital experience analytics, which the Contentsquare pairing makes genuinely distinctive, or if oversight of AI agents matters as much as human QA. Be aware that loris.ai now redirects to Contentsquare and the standalone brand is being absorbed, so buyers who want an independent, single purpose QA vendor with its own roadmap should look at MaestroQA or EvaluAgent instead.
Read the full Loris listing → · See Loris 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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