Veyra offers an AI‑enhanced platform that consolidates production quality data from equipment, sensors, and enterprise systems into a single, real‑time analytics environment. It provides customizable SPC and anomaly‑detection dashboards, a full statistical toolbox, and an AI assistant that guides engineers through configuration and deep‑dive analyses, while supporting collaborative reporting and automated alerts.
Funding
Funding not disclosed
Founders
Product
Problem
Manufacturers often struggle to consolidate quality and process data from disparate sources, leading to delayed detection of process drift, inefficient statistical analysis, and limited visibility into real‑time yield performance.
Solution
Veyra provides a unified, AI‑enhanced platform that aggregates production quality data across equipment, sensors, and enterprise systems into a single analytics environment. The solution delivers customizable SPC and anomaly‑detection dashboards that update in real time, allowing operators to identify and correct drift before scrap occurs. Built‑in statistical tools—including capability indices with non‑normal handling, normality tests, ANOVA, regression, and correlation—enable engineers to perform deep‑dive investigations without exporting spreadsheets. An AI assistant guides users through configuration and analysis, while an agentic playground supports multi‑step explorations that are fully traceable and build on prior sessions. Results are shared via role‑based permissions, in‑app comments, and automated alerts to email, Teams, or Slack, and can be exported as PDF or HTML reports.
Target Audience
Primary customers are manufacturing engineers, quality managers, and process control teams in mid‑size to large industrial plants seeking data‑driven quality improvement, particularly in automotive, metalworking, and cement production.
Features
- Real‑time data ingestion from any source with immediate availability for analysis
- Highly customizable SPC and anomaly‑detection dashboards with alerting to email, Teams, and Slack
- Comprehensive statistical toolbox: Cpk, Pp, Cp (including non‑normal handling), Kolmogorov‑Smirnov normality testing, Box‑Cox and Johnson transforms, ANOVA, regression, and correlation analyses
- AI‑driven assistant for guided setup, configuration, and step‑by‑step deep‑dive analysis
- Agentic Playground for multi‑stage investigations that retain context and knowledge across sessions
- Collaborative features: comments, @mentions, role‑based permissions, full audit trail of changes and decisions
- Exportable PDF and HTML reports with scheduling options for regular distribution