Level AI Contact Center Analytics

Overview

The platform analyzes calls, chats and emails to surface agent and team performance, QA scores, customer satisfaction, call drivers, trends and operational KPIs. Its breadth is useful when teams need to examine interaction data alongside quality results and customer feedback rather than work from separate reporting views.

Level AI also describes itself as a partner for enterprise customer experience teams. That positioning, combined with role-based reporting and custom pricing, makes it a better fit for organizations with established contact center operations than for teams looking for a low-cost, self-serve analytics product.

Key features

Reporting across channels

Custom reports support filters, agent and 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. This gives operations and quality teams several useful angles on performance, although the value depends on how well the platform connects to the systems supplying their data.

Tracked metrics include QA Score, InstaScore, iCSAT, sentiment, customer effort, resolution status, NPS, CSAT, average handle time and first contact resolution. Reports can be scheduled for automatic sharing at customized intervals, while dashboards can be exported as PDFs. Threshold-based alerts can trigger notifications or AI Workers, making changes easier to flag without requiring staff to continually watch dashboards.

AI analysis and access

AI Workers let non-technical users ask questions about contact center data in natural language. This can make analysis more accessible to teams that do not work directly in BI tools, while the API can move contact center data between systems and connect it with business intelligence tools.

Role-based permissions distinguish agents, managers, evaluators and admins: agents can see their own data, managers and evaluators team data, and admins organization-wide data. That separation supports broad reporting without giving every user the same reach.

Security and availability

Level AI states that customer data is not used to train or fine-tune shared models, and that AI subprocessors are contractually prohibited from training on it. Names, card numbers and Social Security numbers are redacted before AI processing. The security page states that data is encrypted with AES-256 at rest and TLS 1.2 or higher in transit. Level AI lists ISO 27001, SOC 2 Type II, HIPAA, PCI DSS, HITRUST and GDPR compliance or certification, with audit documentation through its Trust Center.

The service agreement sets a 99.9% uptime commitment for the Standard Platform and 99.95% for the Enterprise Platform. The higher Enterprise commitment may matter to teams with stricter availability needs; it does not remove the need to confirm which platform and terms apply to a proposed deployment.

Pricing

Level AI Contact Center Analytics: custom pricing; request a demo. No public price is given, so buyers need a quote to assess cost against their interaction volume, users and integration requirements. There are no published seat or usage limits to compare, making commercial terms an important part of evaluation.

The paid product combines analytics, reporting, alerts, AI Workers and role-based access. Teams should weigh that breadth against the effort of confirming which integrations, access controls and API flows their stack requires before committing.

Platforms

Level AI Contact Center Analytics is available on web and through an API. The API is intended to move contact center data between systems and connect it with BI tools; the named integrations include Five9, Amazon Connect, Talkdesk, Genesys, Salesforce, Zendesk, Snowflake and Microsoft Teams. Teams already using these systems have relevant integration paths to assess, but should confirm that their particular data flows are covered.

Who it's for

The strongest fit is a contact center operation that needs shared views of conversation analytics, QA, customer feedback and team performance across calls, chats and emails. Contact center leaders, operations teams, product teams and compliance stakeholders are among the intended users. Organizations that need agent-level and team-level visibility alongside admin oversight can also make use of the role-based reporting model.

It is less compelling for a small team seeking a transparent, low-commitment purchase: pricing is custom, and the product is oriented toward enterprise customer experience teams. Buyers that only need a narrower speech or quality workflow should compare specialist alternatives before adopting a broader platform.

Pros and cons

• Pro: Conversation, QA, feedback and performance data share one analytics platform, supporting cross-channel views of both customer and agent outcomes.
• Pro: Custom reports, scheduled sharing, PDF exports and threshold alerts give operations teams several ways to distribute and act on performance data.
• Pro: Natural-language AI Workers and an API offer paths for both non-technical analysis and BI integration.
• Pro: Role-based views, stated data protections and published uptime commitments address access and operational concerns for enterprise deployments.
• Con: Custom pricing requires a sales conversation, making it harder to assess budget fit early.
• Con: Teams must validate the fit of their specific integrations and data flows; a named integration alone does not establish that every reporting need is covered.

Alternatives

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

• SESTEK Text-to-Speech is a paid API, Linux, self-hosted and Windows option with pay-as-you-go and subscription licensing offered for business usage; consider it when text-to-speech is the need rather than contact center analytics.
• Amazon Connect is a paid service with a free trial and Android, API, iOS and web platforms; its listed SMS and third-party messaging plan charges 0.01 USD per contact, billed per message sent or received, with pricing varying by region and communication type. It is an alternative to consider when those contact channels and trial access matter more than Level AI's analytics focus.
• CallMiner Eureka is a paid API and web product whose pricing depends on user count or interaction volume, enabled modules, integration needs and possibly cloud or hybrid deployment. Consider it when evaluating analytics with those deployment and module variables in view.
• MaxContact Auto QA is a paid API and web product with custom quotes, typically based on conversation volume and flexible monthly or annual contracts. It is worth considering when automated QA and contract flexibility are the main buying criteria.
• Genesys Cloud Agentic Virtual Agent is a paid API and web option with no free plan; its Genesys Cloud CX 1 plan is 75.00 USD per year, billed at $75 USD per user/month annually, with virtual agents included and usage-based pricing potentially applying to AI Experience tokens and certain features. Consider it when virtual agents are the priority rather than unified analytics.
• Scorebuddy Conversation Analytics is a paid API and web product with a free trial and flexible annual contracts for its Foundation plan; consider it when trial access and QA-focused evaluation matter.
• Convin offers a free plan and free trial across Android, iOS and web; its free Quality Management Software plan includes a manual QA platform, auditing templates, automated audit workflow and reporting dashboard. Consider it when starting with free QA tooling is more important than Level AI's broader analytics scope.
• MaestroQA has a free plan and web and extension platforms; its free tier includes 100 Agent Runs per month, unlimited Q&A and $100 in AI Credits. Consider it when those free-tier limits suit an initial evaluation.

Verdict

Level AI Contact Center Analytics is best suited to enterprise contact center teams that need cross-channel performance, quality and customer feedback in one reporting environment. Its combination of custom reporting, AI Workers, role-based access and BI connectivity is the main reason to choose it. Look elsewhere if predictable public pricing or a narrowly focused QA, speech or virtual-agent product is more important than a unified analytics platform.