Tasq develops a machine learning-based task management system that automates work assignment by analyzing SCADA and text data to identify operational issues. This technology enhances decision-making and workflow efficiency by providing actionable insights and eliminating the need for manual data exploration.
Funding
$490K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Industrial operations often struggle with inefficient work assignment due to the need for manual data exploration across disparate SCADA, daily reports, and text-based data sources. This leads to delays in identifying and addressing operational issues, resulting in suboptimal asset performance and increased operational costs.
Solution
Tasq offers an intelligent work management system that automates the identification and assignment of operational tasks by leveraging machine learning to analyze SCADA data, daily reports, and textual information. The platform benchmarks optimal conditions for each asset, enabling prioritized value and proactive issue detection. By scaling knowledge across users and capturing analytics on actions, Tasq facilitates data-driven decision-making and optimized workflows. The system learns from user inputs to improve recommendations, ensuring best practices are consistently applied and performance is continuously enhanced.
Target Audience
Tasq is designed for industrial operations teams, including those in manufacturing, energy, and utilities, who seek to improve work management efficiency and optimize asset performance.
Features
- Automated work identification through machine learning analysis of SCADA, daily, and text data
- Asset-specific models that benchmark optimal conditions for proactive issue detection
- Signal Search, Mass Classification, and Optimization Recommendations tools to eliminate manual data exploration
- Decision intelligence capabilities that scale knowledge across users and capture analytics on actions
- User feedback integration to continuously improve recommendations and ensure effective solutions
- Optimized workflow distribution to connect roles and eliminate organizational bottlenecks
- Performance tracking to monitor the effectiveness of implemented solutions and reduce alarm fatigue