About
Loris is an enterprise-grade conversation intelligence solution that transforms every customer interaction into a rich source of business insight. Rather than relying on manual audits or low-volume surveys, Loris automatically analyzes 100% of conversations across chat, email, and voice channels—whether handled by human agents or AI bots. The platform's core capabilities span three areas. Customer Insights reveals the root causes behind contact volume, tracks sentiment shifts over time, and helps teams anticipate emerging issues before they escalate. Quality Assurance replaces slow, reactive auditing with automated evaluation of every conversation, scoring policy adherence, issue resolution, and agent performance consistently and objectively—linking quality signals to real outcomes like repeat contacts, escalations, and appeasements. AI Agent Analytics provides visibility into how automated agents perform, tracking containment rates, transfers, abandonment, and sentiment so teams can iteratively improve prompts, guardrails, and escalation strategies. Loris is built for customer experience, support operations, and product teams at mid-market to enterprise companies. It integrates with existing CX stacks and surfaces insights that drive measurable outcomes: reduced handling costs, lower repeat contact rates, higher retention, and smarter AI agent deployment. Now operating as Contentsquare's Conversation Intelligence product, it connects conversation data with broader digital experience analytics.
Key Features
- Customer Insights: Analyze 100% of customer interactions to uncover root causes of contact volume, track sentiment over time, and proactively surface emerging issues before they drive churn.
- Automated Quality Assurance: Replace manual spot-checking with automatic evaluation of every conversation for policy adherence, issue resolution, and agent performance—linked to real outcomes like escalations and repeat contacts.
- AI Agent Analytics: Monitor containment rates, transfers, abandonment, and sentiment across AI-handled conversations to continuously improve prompts, guardrails, and escalation strategies.
- Omnichannel Coverage: Ingest and analyze conversations across chat, email, and voice channels regardless of whether they were handled by human agents or AI bots.
- Outcome-Linked Insights: Connect conversation quality signals directly to business outcomes such as repeat contacts, churn risk, appeasements, and revenue impact.
Use Cases
- A customer support operations team uses Loris to automatically QA every agent conversation and identify coaching opportunities without manual auditing.
- A CX analytics team tracks monthly shifts in contact drivers and sentiment to proactively flag product or process issues before they escalate.
- A product team monitors AI chatbot containment and abandonment rates to iteratively improve bot prompts and escalation logic.
- A retention team identifies conversations that correlate with churn risk—such as repeated contacts or unresolved issues—and triggers proactive outreach.
- An e-commerce brand uses conversation insights alongside session replay and product analytics to connect support friction points to drop-offs in the purchase funnel.
Pros
- Full-Coverage Analysis: Analyzes every conversation automatically—not just a sample—delivering statistically reliable insights that manual QA or surveys cannot match.
- Unified Human + AI Visibility: Covers both human-agent and AI-agent interactions in a single platform, making it easy to compare performance and optimize automation strategies.
- Outcome-Linked Quality Scoring: Ties QA scores to measurable business outcomes like escalations and repeat contacts, enabling precise coaching and prioritization.
- Contentsquare Integration: As part of the Contentsquare suite, conversation data can be connected to broader digital experience and product analytics for end-to-end journey insights.
Cons
- Enterprise Pricing: Loris is positioned as an enterprise solution with contact-based pricing, making it potentially cost-prohibitive for smaller support teams.
- No Self-Serve Onboarding: Requires a demo and sales engagement to get started—there is no free trial or self-serve signup available.
- Ecosystem Dependency: Deeper value is unlocked through the Contentsquare ecosystem; teams not already using Contentsquare may need additional integration effort.
Frequently Asked Questions
What types of conversations can Loris analyze?
Loris analyzes chat, email, and voice interactions handled by both human agents and AI-powered bots, giving a complete picture of your customer support operation.
How does Loris differ from traditional QA tools?
Traditional QA tools rely on manual sampling of a small fraction of conversations. Loris automatically evaluates 100% of conversations with consistent, objective scoring and links quality signals to real business outcomes like repeat contacts and escalations.
Can Loris help improve AI agent performance?
Yes. The AI Agent Analytics capability tracks metrics like containment rate, transfer rate, abandonment, and sentiment across AI-handled conversations, providing actionable data to refine prompts, guardrails, and escalation paths.
Is Loris part of Contentsquare?
Yes. Loris now operates as the Conversation Intelligence product within the Contentsquare platform, allowing teams to connect conversation insights with broader digital experience analytics.
What integrations does Loris support?
Loris integrates with existing CX and contact center stacks via APIs and native connectors. It is also part of the Contentsquare ecosystem, which includes integrations with major analytics, marketing, and data platforms.
