Real-time review
Reviewers approve, edit or reject AI output before it ships.
Human-in-the-loop AI — trained reviewers on AI output, escalation of edge cases, prompt and KB feedback loops and 24/7 oversight — so AI never makes unaccountable decisions.
Pure AI pipelines make mistakes faster than anyone can catch them — and pure-manual operations don't scale. Human-in-the-loop (HITL) is the middle ground: AI handles volume, humans handle judgment. Reviewers approve, correct, escalate or override AI output before it reaches customers, systems or records.
Opervics runs HITL AI as a managed function — trained reviewers on AI output, real-time and sampled review modes, edge case escalation, feedback loops into prompts and knowledge bases, and 24/7 oversight for high-risk workflows.
Reviewers approve, edit or reject AI output before it ships.
Post-hoc sampling for lower-risk workflows — measured and trended.
Uncertain, ambiguous or high-risk cases routed to trained reviewers.
Review findings turned into prompt, rule and KB improvements.
Round-the-clock review for high-risk or customer-facing workflows.
Approval rate, edit rate, override rate, escalation rate and quality trend.
These are the same operational issues we see across clients — and the same ones our process is designed to remove.
Output ships with no human owner — errors reach customers first.
Internal teams can't keep up with AI output volume — review backlog grows.
Different reviewers apply different rules — quality varies wildly.
Review findings never make it back into prompts, rules or KB.
AI makes decisions in regulated or sensitive areas with no oversight.
Nobody knows approval, edit or override rates over time.
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 access controls defined with your team.
Every reviewer action logged and sampled for quality.
Approval rate, edit rate, override rate and quality trend reported weekly.
AI handles volume and drafts — trained human reviewers approve, edit, escalate or override before output ships. AI never makes unaccountable decisions.
Real-time for customer-facing, regulated or high-risk workflows. Sampled for lower-risk internal pipelines where post-hoc QA is enough.
OpenAI, Anthropic, Google, open-source models — plus Zendesk, HubSpot, Salesforce, custom apps and internal admin panels.
Yes — every review finding is turned into prompt, rule and KB updates that reduce future errors.
Approval rate, edit rate, override rate, escalation rate and quality trend — reported weekly.
Per volume band, per workflow, or as a monthly retainer — agreed upfront.
A short conversation is usually enough to scope the workflow and propose a starting point.