Scoop Analytics uses AI to diagnose operational performance, identify root causes, and deliver actionable plans to managers in distributed businesses.
Scoop Analytics is an AI-powered performance management platform designed for distributed businesses with multiple locations. It extends traditional Business Intelligence (BI) by not just showing what happened, but also why it happened and what actions to take. The platform codifies the judgment of a business's best operators into an AI model that automatically scans operating performance at every location, delivering plain-language action plans to managers. Scoop integrates with existing BI stacks like Power BI, Tableau, and Looker, layering on top without requiring a new tool for teams to learn. It automates 95% of diagnostic work, allowing BI teams to focus on higher-value projects. The system provides role-specific action plans, tracks their effectiveness, and feeds that signal back into the playbook, aiming to close performance gaps across the network. It supports private deployment, allowing data to remain within the client's governance boundary, and offers data portability. The platform is designed for industries such as retail, food & beverage, hospitality, franchise businesses, and private equity rollups. It aims to improve bottom-quartile locations first, raising the overall performance floor. Scoop offers predictable inference costs and a fast time to value, with pilots typically deployed in about four weeks.
Integrations: Power BI, Tableau, Looker, Snowflake, BigQuery, Redshift
Platforms: Web
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