AI-assisted ticket handling
AI drafts replies, classifies tickets and suggests next steps.
AI-assisted customer support — AI agents drafting and triaging, specialists reviewing and owning — with human-in-the-loop QA, agent monitoring and knowledge base training.
AI customer support works — when it's set up as an assist, not a replacement. Untrained bots, unmonitored AI agents and inaccurate knowledge bases damage customer trust faster than they save cost. The teams that get value from AI support treat it as a layer on top of trained humans.
Opervics runs AI customer support with a human-in-the-loop model — AI agents draft, classify and triage; trained specialists review, edit and own every customer-facing response. AI never replaces accountability.
AI drafts replies, classifies tickets and suggests next steps.
Every AI-assisted response reviewed and owned by a specialist.
Accuracy, tone, escalation rules and hallucination checks tracked.
KB curated, cleaned and structured for AI retrieval accuracy.
Clear rules for when AI handles, hands off or escalates to a human.
AI deflection rate, accuracy, escalation rate, CSAT and cost per ticket.
These are the same operational issues we see across clients — and the same ones our process is designed to remove.
Bots answer inaccurately — customer trust drops fast.
AI confidently gives wrong information with no human review.
AI decisions run without review — quality and risk both drift.
Stale or unstructured KB — AI retrieves the wrong content.
AI doesn't know when to hand off — customers get stuck.
Nobody knows deflection rate, accuracy or CSAT impact.
Every service inherits the same baseline security posture, then adds service-specific controls on top.
Access, change management, monitoring and incident response aligned to SOC 2.
PII handling, redaction and prompt-safety rules defined with your team.
Every AI-assisted queue reviewed by trained specialists.
Deflection rate, accuracy, escalation rate and CSAT reported weekly.
No — AI assists with drafts, triage and classification. Trained specialists review, edit and own every customer-facing response.
OpenAI, Anthropic, Google and open-source models — integrated with Zendesk, Intercom, HubSpot, Freshdesk and Help Scout.
Human-in-the-loop review, KB grounding, accuracy sampling and escalation rules that route uncertain cases to a person.
Yes — KB curation, cleanup and structuring is a core part of AI support quality, and usually improves deflection rates.
AI deflection rate, accuracy sampling, escalation rate, CSAT and cost per ticket — reported weekly.
Per ticket, per FTE, or as a monthly retainer — agreed upfront.
A short conversation is usually enough to scope the process and propose a starting point.