Level AI Contact Center Analytics

Level AI Contact Center Analytics brings calls, chats, and emails together with QA scores, customer feedback, and performance measures to help teams review contact center results. It tracks metrics such as QA Score, InstaScore, iCSAT, sentiment, customer effort, resolution status, NPS, CSAT, average handle time, and first contact resolution. Users can build reports with filters, agent or team groupings, comparisons, KPI tracking, and historical trends. Built-in dashboards cover QA performance, coaching, auditor performance, Voice of the Customer, and conversation insights. AI Workers let non-technical users ask natural-language questions about contact center data. Reports can be scheduled for sharing, and threshold-based analytics alerts can trigger notifications or AI Workers. Dashboards export as PDFs, while role-based permissions provide different data access for agents, managers, evaluators, and admins. Its API can move contact center data between systems and connect with business intelligence tools. Listed integrations include Five9, Amazon Connect, Talkdesk, Genesys, Salesforce, Zendesk, Snowflake, and Microsoft Teams. Pricing is available on request.

Level AI Contact Center Analytics combines conversation data, quality measures, and operational reporting in one platform. Consider its request-based pricing and range of reporting and access controls when assessing fit.

The analytics platform is intended for contact center leaders, operations teams, product teams, and compliance stakeholders who need reporting across conversations and performance measures.

Level AI Contact Center Analytics is a multichannel reporting platform for organizations that need to connect conversation quality, customer feedback, and operational results. It suits established contact-center, operations, product, and compliance teams more than small groups seeking a self-serve tool. The main decision is whether its configurable analytics and enterprise controls justify a quote-based purchase.

Overview

The service analyzes calls, chats, and emails together with QA scores, customer feedback, and performance measures. It is designed to expose agent and team performance, call drivers, trends, and contact-center KPIs in a shared view. That unified model is useful when quality and customer outcomes need to be examined alongside interaction data instead of in separate systems.

Level AI describes an enterprise customer-experience focus. Role-based reporting can give agents their own results, managers and evaluators team-level views, and administrators organization-wide access. Buyers needing differentiated access and formal governance will get more from it than teams shopping for a low-cost analytics dashboard.

Key features

Reporting and dashboards

Custom reports support filters, agent or team groupings, performance comparisons, KPI tracking, and historical trends. Built-in dashboards cover QA Performance, Coaching, Auditor Performance, Voice of the Customer, and Conversation Insights. Metrics include QA Score, InstaScore, iCSAT, sentiment, customer effort, resolution status, NPS, CSAT, average handle time, and first contact resolution. The breadth supports quality reviews and operational diagnosis, although its usefulness depends on how well the integrations reflect a company’s data model.

AI analysis and automation

AI Workers let nontechnical users ask natural-language questions about contact-center data. Scheduled reports can be shared automatically, while threshold-based alerts can notify people or trigger AI Workers. These features can reduce repetitive monitoring and help teams move from a dashboard finding to a follow-up action without requiring every stakeholder to write queries.

Agent and conversation capabilities

The offering includes real-time guidance, suggested replies, knowledge retrieval, conversation summaries, next-best actions, sentiment analysis, real-time monitoring, speech analytics, and quality scorecards. Because supported channels are multichannel, the same analytics approach can span voice and digital interactions rather than limiting review to calls.

Connections, exports, and protection

Integrations include Five9, Amazon Connect, Talkdesk, Genesys, Salesforce, Zendesk, Snowflake, and Microsoft Teams. The API can move contact-center data between systems and connect it to business-intelligence tools. Dashboards export to PDF, and role-based permissions separate agent, manager, evaluator, and administrator access.

Level AI lists ISO 27001, SOC 2 Type II, HIPAA, PCI DSS, HITRUST, and GDPR compliance or certification, with audit documentation in its Trust Center. Names, card numbers, and Social Security numbers are redacted before AI processing; data uses AES-256 encryption at rest and TLS 1.2 or higher in transit. Customer data is not used to train shared models, and AI subprocessors are contractually barred from training use.

Pricing

The Level AI Contact Center Analytics plan uses custom pricing; buyers must schedule a demo. There is no public seat price, quota, free plan, or trial term to compare, so budget and renewal terms should be settled during contracting. The service agreement commits to 99.9% uptime for the Standard Platform and 99.95% for the Enterprise Platform. That distinction matters for teams making availability guarantees part of procurement.

Platforms

Level AI Contact Center Analytics is offered through web and API access. The API is particularly relevant to organizations that need to feed analytics into existing business-intelligence or operational systems.

Who it's for

Contact-center leaders and operations teams can use the reporting, alerts, scorecards, and historical comparisons for continuous performance management. Product teams can examine call drivers and customer signals, while compliance stakeholders benefit from permissions, redaction, encryption, and documented security controls. It is less suitable for a small operation that requires transparent pricing and a lightweight, self-directed setup.

Pros and cons

• Pros: Calls, chats, emails, QA, feedback, and performance metrics share one analytics layer.
• Pros: Natural-language AI Workers, scheduled reports, and threshold alerts make recurring analysis more actionable.
• Pros: Broad integrations, an API, PDF exports, and role-based access support complex enterprise workflows.
• Pros: Extensive security and privacy controls address regulated contact-center environments.
• Cons: Pricing is entirely quote-based, making upfront comparison difficult.
• Cons: Standard and Enterprise uptime commitments differ, so the contracted platform tier matters.

Alternatives

Choose Convin if a free plan, free trial, and a manual-QA platform with automated audit workflow are priorities. Choose JustCall Speech Analytics when published per-user tiers matter: Team is $29 a month billed annually with a two-license minimum, Pro is $49, and Pro Plus is $89. SESTEK Text-to-Speech is an option for API, Linux, self-hosted, or Windows deployments with pay-as-you-go or subscription licensing. QEval suits buyers wanting a quoted deployment from ETS Labs. Consider AmplifAI Quality Assurance, Feelingstream, or MaxContact Auto QA when their respective deployment approaches better match your stack. Xdroid Customer Interaction Intelligence Platform requires a demo and has a 25-agent minimum.

For broader category comparisons, see Call Center Speech Analytics Software, Agent Assist Software, Contact Center Analytics Software, Customer Experience Analytics Software, Customer Interaction Analytics Software, and Speech Analytics Software.

Verdict

Level AI Contact Center Analytics is a strong choice for enterprise contact centers that need cross-channel analytics, configurable quality reporting, AI-assisted investigation, and controlled access in one system. Its main reason to choose it is the combination of unified metrics and operational automation. Look elsewhere if transparent pricing, a free tier, or a smaller-team buying path is essential.