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UptimeAI co-founder Jagadish Gattu
San Francisco-based AI startup UptimeAI, which also has offices in Bengaluru and Houston, has raised $14 million in a Series A funding round.
WestBridge Capital led the round, with participation from existing investor Emergent Ventures and new investor Aditya Birla Ventures and Sequoia Capital India.
Purpose of fundraising
With this round of funding, UptimeAI aims to scale up its technology platform and expand its product portfolio. The startup will also be focusing on extending its market presence in North America, the Middle East, and Asia.
Furthermore, the startup plans to accelerate product development and hire top talent in AI and machine learning to strengthen its team.
“Our vision is to embed the expertise of a seasoned Subject Matter Expert into a self-learning AI solution. With 90% of our revenues from the US and Middle East markets, this funding validates our go-to-market and product strategy and enhances our offering significantly,” said Jagadish Gattu, CEO of UptimeAI.
What does UptimeAI do?
Founded in 2019 by Jagadish Gattu and Vamsi Yalamanchili, UptimeAI specializes in AI-powered solutions for manufacturing plants.
The startup has developed an AI-driven platform that monitors and optimizes plant operations using advanced machine-learning algorithms to predict equipment failures, improve efficiency, and reduce downtime.
“Our AI solution not only predicts equipment failures before they occur, but also identifies inefficiencies and suggests optimizations to improve performance. This approach significantly reduces any unplanned downtime, ultimately enhancing operational reliability and efficiencies - paving the way for a smarter, more resilient future,” he added.
UptimeAI claims that its solutions have already been adopted by several Fortune 500 companies across various sectors, including energy, chemicals, and heavy industries, demonstrating significant improvements in plant reliability and performance.
Offering four modules
UptimeAI offers four core modules: connect the dots, no-code predictive alerts, an inferencing engine for prescriptive actions, and continuous self-learning.
The startup boasts a patented system and method for monitoring complex structures to identify the root cause of inefficiencies. These solutions have led to substantial improvements in operational efficiency for its clients, with some reporting up to a 20% reduction in unplanned downtime.