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About
Loris AI CX Quality is an enterprise-grade conversation intelligence platform designed to help customer experience teams extract actionable insights from every customer interaction—whether handled by humans or AI agents. By automatically analyzing chat, email, and voice conversations at scale, Loris eliminates the guesswork of traditional sample-based quality audits and survey-driven feedback loops. The platform's core capabilities span three key pillars. Customer Insights surfaces the root causes behind contact volume, identifies sentiment trends, and reveals emerging issues before they escalate—empowering teams to reduce repeat contacts and churn. Quality Assurance automates evaluation of policy adherence, issue resolution, and agent performance, linking quality signals to real business outcomes like escalations and appeasements so managers can coach with precision. AI Agent Analytics provides visibility into how AI-handled conversations perform, tracking containment rates, transfers, abandonment, and sentiment to continuously improve automation strategies. Loris is built for CX leaders, QA managers, and operations teams at mid-to-large enterprises who need a scalable, objective way to maintain service quality as conversation volumes—and AI adoption—grow. It integrates with existing contact center stacks to deliver end-to-end journey intelligence without adding manual overhead. The result is lower support costs, higher customer loyalty, and smarter deployment of both human and AI agents.
Key Features
- Customer Conversation Insights: Analyzes 100% of customer interactions to uncover root causes behind contact volume, track sentiment shifts over time, and identify emerging issues before they escalate.
- Automated Quality Assurance: Replaces slow manual QA audits with automatic evaluation of every conversation, scoring policy adherence, issue resolution, and agent performance consistently and objectively.
- AI Agent Analytics: Tracks containment, transfers, abandonment, and sentiment for AI-handled conversations, enabling teams to refine prompts, guardrails, and escalation strategies.
- Outcome-Linked Quality Signals: Connects QA scores to real business outcomes—like repeat contacts, escalations, and appeasements—so coaching and improvements are tied to measurable impact.
- Omnichannel Coverage: Supports analysis across chat, email, and voice channels, providing a unified view of the entire customer conversation landscape.
Use Cases
- Automating quality assurance across thousands of daily customer conversations to replace slow, manual review processes.
- Identifying the root causes of high contact volume to reduce repeat contacts and lower operational costs.
- Monitoring AI agent performance in real time to improve containment rates and escalation strategies.
- Coaching customer service agents with data-backed feedback tied to actual resolution and satisfaction outcomes.
- Detecting emerging customer issues and sentiment shifts early to proactively prevent churn and escalations.
Pros
- 100% Conversation Coverage: Unlike sample-based QA, Loris evaluates every interaction automatically, eliminating blind spots and delivering statistically reliable insights.
- Proactive Issue Detection: Surfaces emerging problems and sentiment trends in real time, allowing teams to act before issues escalate into churn or reputational damage.
- AI Agent Performance Visibility: Provides dedicated analytics for AI-handled conversations, a critical differentiator as automation becomes central to customer service operations.
- Precision Coaching: Links quality signals to outcomes, enabling managers to coach agents on the behaviors that actually drive resolution and customer satisfaction.
Cons
- Enterprise-Focused Pricing: Loris is built for mid-to-large enterprises, making it potentially cost-prohibitive for smaller teams or startups with lower conversation volumes.
- Implementation Complexity: Integrating Loris with existing contact center platforms and data sources may require technical resources and onboarding time.
- No Self-Serve Free Tier: There is no publicly available free plan or trial, meaning teams must engage with sales before evaluating the platform.
Frequently Asked Questions
What types of customer conversations does Loris analyze?
Loris analyzes chat, email, and voice conversations—covering both human-agent and AI-agent-handled interactions across your contact center.
How is Loris different from traditional QA tools?
Traditional QA tools rely on manual review of a small sample of conversations. Loris automatically evaluates 100% of interactions with consistent, objective scoring, and links quality signals to real business outcomes like escalations and repeat contacts.
Can Loris help us manage and improve AI agents?
Yes. Loris's AI Agent Analytics module tracks key metrics like containment rates, transfer rates, abandonment, and customer sentiment for AI-handled conversations, helping you continuously optimize prompts, guardrails, and escalation flows.
What integrations does Loris support?
Loris integrates with existing contact center platforms and CX tech stacks via its API. Specific integrations are available through their platform—contact Loris for a full list of supported systems.
Who is Loris best suited for?
Loris is best suited for mid-to-large enterprises with high-volume customer service operations, including CX leaders, QA managers, and operations teams looking to scale quality management without increasing headcount.
