AI QA Agent Evaluation

Automated evaluation of every agent's calls against QA parameters — providing per-call scores, trend analytics, peer benchmarking, and coaching recommendations for every agent, not just those whose calls were randomly selected for manual review.

Convin integrates with existing telephony via API, captures 100% of call audio, transcribes it in real time, and applies ML-based QA scoring models against configurable quality frameworks. QA scores, deviation flags, and post-call coaching recommendations are delivered to dashboards within 60 minutes of call completion — no manual call listening required.

Manual agent evaluation covers 3–5 calls per agent per month. AI evaluation covers every call — providing fair, objective, complete performance data for every agent.

Per-call evaluation for every agent across every shift, objective scoring, peer benchmarking, improvement trend analysis, and targeted coaching recommendations based on where each agent's scores are lowest. Speak to a Convin product specialist at convin.ai/demo.

Insurance (IRDAI compliance QA on every renewal and claims call), BFSI/NBFCs (RBI collections quality scoring and audit trail generation), EdTech (admissions counsellor QA for UGC/DPDP compliance), healthcare (patient communication quality monitoring), and e-commerce (high-volume support QA for FCR and tone compliance).

Traditional QA reviews 2-5% of calls, takes 24-72 hours to produce results, and relies on reviewer consistency. AI QA Agent Evaluation scores 100% of interactions automatically, delivers results within 60 minutes, and applies the same standards consistently to every call — without reviewer availability constraints.

ASR for 100% voice transcription, NLP for quality signal and compliance deviation detection, ML-based QA scoring models trained on contact centre interaction data, automated deviation flagging with timestamp and agent ID, post-call coaching recommendation generation, and tamper-proof audit log creation.

Yes. QA at 100% coverage — rather than 2-5% sampling — ensures that quality improvements identified through scoring actually propagate to all agent interactions. Convin QA customers report 17% CSAT improvement and 21% FCR improvement as consistent quality management drives better agent behaviour across the team.

Yes. 80% reduction in manual QA effort is the primary cost reduction. Higher-quality QA data drives faster coaching improvement, which produces 28% AHT reduction and 21% FCR improvement — eliminating the repeat-contact and handling cost of unresolved interactions.

Via API integration with existing telephony (Genesys, Avaya, Cisco, AWS Connect) and CRM (Salesforce, HubSpot, Zoho) — 2-3 week deployment timeline managed by Convin's customer success team. No rip-and-replace of existing infrastructure required. QA scorecards, compliance rules, and coaching frameworks are configured during onboarding. Speak to a Convin product specialist at convin.ai/demo.