Accuracy scoring
Every sampled output scored against ground truth and source material.
AI output QA — human review of AI-generated content, accuracy scoring, hallucination flags, brand tone checks and safety review — so AI output is trustworthy before it reaches anyone.
AI output drifts. Factual errors, hallucinated claims, off-brand tone, safety issues and subtle inaccuracies leak into content, replies and internal workflows — often without anyone noticing until it reaches a customer, a regulator or a published page.
Opervics runs AI output QA as a managed function — human review of AI-generated content, accuracy scoring against ground truth, hallucination flags, brand tone checks and safety review — so AI output is trustworthy before it reaches anyone.
Every sampled output scored against ground truth and source material.
Unsupported claims identified, logged and routed for correction.
Off-brand, robotic or inconsistent replies flagged with examples.
Outputs checked against safety, legal and compliance rules.
Issues turned into prompt, KB and rule adjustments with your team.
Accuracy score, hallucination rate, brand flags and safety issues.
These are the same operational issues we see across clients — and the same ones our process is designed to remove.
AI output published or sent without human review.
Confident but wrong claims slip through to customers or pages.
AI content sounds robotic or inconsistent with your voice.
Policy violations or unsafe content go unnoticed until audit or complaint.
Errors are found but never turned into prompt or KB improvements.
Nobody knows accuracy, hallucination rate or brand compliance.
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 content-safety rules defined with your team.
Every sampled output reviewed by trained specialists.
Accuracy score, hallucination rate, brand flags and safety issues reported weekly.
Human review of AI-generated content, accuracy scoring against ground truth, hallucination flags, brand tone checks, safety review and correction loops.
Customer replies, marketing and product copy, internal knowledge content, code comments and any AI pipeline output you route to us.
Both — we flag issues with corrected examples and support prompt, KB and rule adjustments with your team.
Sampled outputs are scored against your source material, policies and ground truth — with scores trended over time.
Accuracy score, hallucination rate, brand compliance, safety flags and correction trends — reported weekly.
Per volume band, per AI surface, or as a monthly retainer — agreed upfront.
A short conversation is usually enough to scope the AI surface and propose a starting point.