Format & field checks
Format, pattern, and required-field validation on every record.
Opervics runs data validation as a managed function — field-level checks, deduplication, business-rule validation and exception handling before anything reaches your CRM, ERP or reporting layer.
Bad data is expensive — but it's cheapest to catch before it enters your systems. Data validation is the checkpoint between raw intake and system entry: field-level checks, business-rule validation, deduplication and structured exception handling.
Opervics runs data validation as a managed function. Documented validation rules are applied to every record; exceptions are logged, routed and corrected; QA sampling reports accuracy and error rates weekly.
Format, pattern, and required-field validation on every record.
AI-assisted detection of duplicates across records and sources.
Validation against your business rules and reference data.
Structured logging, routing and correction of invalid records.
Every rule written down and versioned — auditable.
Accuracy, error rates, exception volume — reported weekly.
These are the same operational issues we see across clients — and the same ones our process is designed to remove.
Errors enter your systems and cause downstream problems.
Duplicate customers, vendors, or transactions across sources.
Data arrives in mixed formats, breaking downstream automation.
Business rules documented but not actually checked.
Invalid records disappear without correction or follow-up.
Nobody knows error rates or where validation is failing.
Every service inherits the same baseline security posture, then adds service-specific controls on top.
Encryption in transit and at rest, role-based access, and least-privilege workflows across every account.
NDA-bound teams, restricted environments, and auditable access logs for regulated services.
AI output is reviewed by trained specialists before it reaches your systems — no blind automation.
Service-specific SLAs, tracking, and audit-ready reporting from day one.
Format and pattern checks, required-field validation, value-consistency checks, business-rule validation, deduplication and exception handling.
Invalid records are logged, routed to a structured exception queue, and either corrected or flagged for your team. Nothing disappears silently.
Every rule is written down and versioned. Changes are tracked, so you can audit which rules were active at any point in time.
Yes. We validate against your internal reference data — customer master, vendor master, product catalogue — or external sources as needed.
Accuracy, error rates and exception volumes reported weekly, with QA sampling on every batch.
Per record, per batch, per FTE, or as a monthly retainer — agreed upfront with no hidden add-ons.
A short conversation is usually enough to scope the process and propose a starting point.