CoreVQ Services

• Integrate a customer-selected or purpose-built AI-based quality score into CoreVQ results and exports
• Add frame-level detection, classification, segmentation, OCR, content understanding, or specialized defect analysis
• Support specialized media formats, metadata, test cases, score presentation, and operator workflows
• Define model rights, inputs, outputs, confidence, coverage, validation evidence, performance, and provenance

Customer-specific implementation is delivered through Services. Reusable third-party plugin distribution remains subject to the planned SDK contract and applicable model licenses.

• Combine CoreVQ and customer-selected scores into qualification rules, rendition ranking, anomaly triage, and encoding recommendations
• Develop media intake, job orchestration, scheduling, evidence storage, reporting, dashboard, alerting, and escalation components
• Build custom qualification tools, monitoring workflows, and operator views for the customer's product and organization
• Engineer throughput, concurrency, latency, resilience, storage, and infrastructure cost for the required production scale

The deliverable is an implemented and qualified workflow with customer-specific logic, integration components, deployment guidance, and handoff. Embedding CoreVQ in a customer-distributed product requires a qualified SDK package and a separate written SDK agreement.

• Compare codecs, encoder presets, resolutions, content classes, bitrates, and adaptive-bitrate ladders
• Identify operating points that maximize measured QoE within bitrate, latency, compute, storage, and delivery-cost constraints
• Measure quality-per-bit, analysis throughput, infrastructure demand, and scalability across the target content volume
• Deliver reproducible evidence, findings, recommended configurations, and clearly stated operating limits

The customer receives a decision-ready engineering report or a repeatable analysis workflow for continued optimization.