Move quality management from limited manual reviews to continuous visibility across customer interactions. Orvera AI helps teams understand service quality across voice, chat, email, AI agents, Agent Assist, and human-led conversations without depending only on random sampling.
Analyze inbound calls, outbound calls, chats, emails, and assisted interactions
Review AI bot conversations, human agent conversations, and Agent Assist workflows
Track quality across campaigns, departments, queues, processes, and channels
Expand QA coverage while keeping supervisors and quality teams in control
Create quality standards that match the way each enterprise process actually works. Orvera AI’s QM adapts parameters, weights, pass/fail logic, and compliance rules according to the industry, organization, channel, and workflow being measured.
Define criteria for greeting, active listening, problem resolution, compliance disclosure, professionalism, closing, and more
Configure weights, thresholds, required parameters, and fatal compliance checks
Support industry-specific standards, enterprise SOPs, campaign rules, and department-level workflows
Keep QA consistent while allowing each process to have its own quality definition
Unify quality management across every type of service execution. Whether the interaction is handled by an AI voice agent, a chat agent, a human agent, or a human agent supported by Agent Assist, Orvera AI applies structured QA to understand what happened and how well the process was followed.
Evaluate AI agents taking calls, chats, emails, or process-driven conversations
Run separate auto-QA for human agents making or receiving calls
Review Agent Assist performance by comparing guidance, agent behavior, and interaction outcomes
Compare quality performance across automation, assisted service, and human teams
Make every quality score explainable and reviewable. Orvera AI connects weighted scores, criteria results, compliance outcomes, and sentiment to the exact interaction evidence behind them, helping supervisors understand why a conversation passed, failed, or needs review.
View weighted average, criteria met, compliance status, and sentiment in one QA record
See parameter-level feedback for every evaluated criterion
Link scores to transcript evidence, customer statements, agent responses, and interaction summaries
Understand whether failures came from script gaps, missed disclosures, weak resolution, or agent execution
Identify the patterns that explain performance across teams, processes, and channels. Orvera AI shows where customer interactions are breaking down, why compliance is failing, and which behaviors most affect service quality.
Detect missed compliance disclosures, incomplete greetings, weak closings, and unresolved interactions
Identify recurring issues across campaigns, bots, agents, queues, and departments
Separate tone and professionalism issues from process and compliance failures
Prioritize the quality gaps most likely to affect customer experience, audit readiness, and operational performance
Convert quality findings into focused operational action. Orvera AI helps teams move from scorecards and reporting into coaching, workflow refinement, bot improvement, and process governance.
Coach human agents using clear feedback and transcript-backed evidence
Improve AI agent prompts, scripts, disclosures, routing, and handoff behavior
Refine workflows where QA reveals repeated friction, unresolved requests, or missed next steps
Track whether quality, compliance, and resolution improve after changes are made
Make quality performance visible, measurable, and decision-ready for leadership. Orvera AI gives operations, CX, compliance, and contact center leaders one place to understand how service is being executed across the enterprise.
Bring quality scores, compliance results, sentiment, criteria trends, and interaction evidence into dashboards
Compare performance across AI agents, human agents, teams, channels, campaigns, and processes
Track QA trends across voice, chat, email, and Agent Assist workflows
Support governed access, auditability, reporting, and enterprise quality oversight
Calls, chats, emails, transcripts, campaign data, Agent Assist activity, and human-agent interactions are brought in from service channels and systems.
Enterprise standards are mapped into process-specific scorecards with parameters, weights, thresholds, and compliance rules.
Interactions are analyzed for greeting, disclosure, active listening, problem resolution, professionalism, closing, sentiment, and custom criteria.
Each QA record includes weighted average, criteria met, compliance status, parameter feedback, and evidence from the interaction.
Dashboards, reports, exports, and coaching views help leaders improve service quality, compliance, automation, and team performance.
Orvera AI is an enterprise-ready conversational AI platform, built on 18+ years of contact center leadership experience and designed to deliver structured resolution, stronger customer experience, and measurable performance.
