Infrastructure automation platform Adaptive raises pre-seed funding round led by Antler India
Founded in 2021 by serial entrepreneur and Brown University alum, Ronak Massand and DevOps engineer Debarshi Basak, Adaptive aims to empower technical stakeholders to build DevOps solutions using out-of-the-box templates and functions
NEW DELHI: Infrastructure automation platform Adaptive has raised pre-seed funding from Antler India, Pareto Holdings, Adept Ventures, Hustle Fund, and Haresh Chawla to transform the current state of DevOps and infrastructure management for software companies.
Adaptive aims to improve developer productivity and facilitate better collaboration by simplifying building DevOps solutions. The startup allows companies to build customisable internal DevOps platform apps.
Founded in 2021 by serial entrepreneur and Brown University alum, Ronak Massand and seasoned DevOps engineer Debarshi Basak, Adaptive aims to empower technical stakeholders such as engineering managers, devops engineers and site reliability engineers (SREs) to build DevOps solutions using out-of-the-box templates and functions. The founders have earlier built US-based Parkloco that was eventually acquired by Silicon Valley based robotics company, Volley Automation.
“…at Adaptive, we are building the modern-day orchestration technology from ground up. We are going after a $70bn+ process automation market globally," said Ronak Massand, co-founder of Adaptive.
Commenting on the investment, Nitin Sharma, Partner at Antler India, said,“We’re especially excited about how Adaptive is approaching an extremely hard problem to solve - i.e. building a modern-day orchestration technology from ground up."
Antler is one of the fastest growing VC firms in the world and plans to deploy $100M to $150M in 100+ Indian startups over the next three years.
In 2021, 50% of $3.1 trillion spent on IT was directed towards support and operations. Additionally, an average developer spends about 55% of their time on managing existing code. Most companies try to solve this problem through an expensive and unscalable internal platform solution.
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