Small Retailer
Data You Can Trust
Business decisions rely on accurate data. V9 continuously validates incoming data, detects anomalies, and manages corrections automatically, ensuring your analytics remain trustworthy across every device, store, and reporting system.
Continuous Data Validation
Every data stream is automatically verified as it arrives. V9 checks device health, transmission completeness, and expected patterns before accepting the data into reporting pipelines. Suspicious or incomplete datasets are flagged immediately, preventing compromised information from silently affecting operational dashboards or management reports.
Intelligent Anomaly Detection
Unexpected spikes, sudden drops, or abnormal traffic patterns are automatically detected. V9 analyses historical trends and cross-site benchmarks to identify potential data anomalies. When detected, alerts are triggered so teams can investigate whether the change reflects a genuine operational event or a device-level issue.
Flexible Aggregation Engine
Retail and enterprise environments often experience delayed data transmission. V9’s aggregation engine intelligently handles late-arriving data, retries failed uploads, and automatically recalculates historical aggregates when necessary. This ensures hourly, daily, and weekly metrics remain accurate even when devices reconnect or data arrives after initial reporting.
Integrity Scores & Data Status
Every dataset includes a transparent integrity status. Reports, APIs, and exports indicate whether data is validated, awaiting completion, or affected by anomalies. This ensures analysts and BI systems always understand the reliability of the dataset before making operational or strategic decisions.
Health Monitoring & Recovery
V9 continuously monitors device connectivity, data flow, and model accuracy across the entire network. When issues occur, alerts are triggered and recovery workflows begin automatically. If required, data correction or patching can be applied in a controlled and fully documented process.
Model Validation Workspace
AI models powering people counting and analytics are continuously benchmarked using validation tools. V9 allows teams to compare model output against ground-truth data, detect accuracy drift across locations, and fine-tune models for specific environments. This human-in-the-loop validation ensures analytics remain consistent across different stores, lighting conditions, and operational setups.
AI Model Validation & Benchmarking
Governance Built-In
Reliable analytics require more than accurate devices. V9 embeds governance directly into the data pipeline - validating inputs, monitoring anomalies, managing corrections, and transparently reporting data integrity so organisations can make confident, data-driven decisions.