Summary
Aperio is the leader in operational data integrity. The company provides AI-powered data observability and quality solutions to help customers drive profitable and sustainable operations. They aim to become a system of record, prioritizing critical data issues related to data quality, sensor monitoring, and data wrangling.
Problem
According to McKinsey data quality is a consistent roadblock for the highest-value AI use cases among industrial companies with asset-intensive operations. Legacy system architecture and weak data governance also contribute to the data quality challenges.
Like past generations of data engineers in IT, OT analytics teams have often built their ad-hoc tools to address data quality issues. However, data quality tools take time to build, face useability challenges, and have limited coverage. Since OT comprises complex systems with many points of failure, an in-house end-to-end data quality tool is difficult to create and maintain.
Solution
Aperio offers an AI-driven SaaS platform called Aperio DataWiseÔ that automates the validation of operational data in industrial organizations. It addresses data completeness, content, and metadata context, using AI and ML to scale and prioritize data quality issues. The platform enables monitoring and validation and provides actionable insights for data quality improvement.
Why It Matters
Aperio's solution fills a gap that in-house solutions cannot address. They help industrial companies make smarter data-driven decisions, improve profitability, sustainability, and mitigate risks associated with poor data quality.
Aperio estimates that investing in their software, reducing just a few outages, or improving reporting accuracy, can provide an ROI of 20-40x.
Aperio is capitalizing on a market inflection point. They have built a category-leading Data Integrity platform, a 'must-have' solution for top asset-intensive industries dealing with data challenges at scale.
