Harness, a B2B startup founded by Jyoti Bansal and Rishi Singh, has raised $60 million in Series B funding led by IVP, Google Ventures (GV), and ServiceNow Ventures. Existing investors Menlo Ventures and Unusual Ventures also participated in the round.
Harness, which is in the space of continuous delivery-as-a-service platform, is headquartered in San Francisco with a R&D centre in Bengaluru. According to the company, it will use this new round of funding to expand investment in R&D and scale its rapidly growing engineering, sales, and customer success teams. Prior to this funding round, Harness had raised $20 million in Series A.
"We were not actively seeking new investment at this point, but our strong market traction created heavy investor interest in Harness, resulting in a fast-moving and heavily oversubscribed Series B round," said Jyoti Bansal, CEO and Co-founder of Harness.
"Harness represents a tremendous opportunity to create the next multi-billion dollar company. The team has a powerful vision to redefine the software delivery process using automation and Machine Learning (ML), and the company's market momentum is significantly beyond what we typically see in companies at this stage," said Steve Harrick, General Partner at IVP.
The technology platform of Harness uses advanced ML and Artificial Intelligence (AI) to automate software deployments, analyse their quality, and automatically roll back if something goes wrong.
Jyoti Bansal was the former CEO and Founder of AppDynamics, an application monitoring company acquired by Cisco for $3.7 billion in 2017. Rishi Singh is a former DevOps platform architect at Apple.
According to Harness, since launching from stealth in October 2017, it has experienced tremendous growth and helped dozens of customers such as McAfee, Home Depot, SoulCycle, Bank of Santander, NCR, and Beachbody significantly improve their ability to deliver software changes in modern cloud and container architectures.
The startup claimed that customers typically see immediate gains with Harness that include reduction in deployment times from many weeks to just a few hours, reduction of deployment-related errors by 95-99 percent, and a three to four times increase in DevOps team efficiency.