Sift raises $17.5m Series A for hardware sensor data platform

The round was led by Google Ventures and brings Sift’s total funding to $25 million. The investment will be used to increase its staff, build up its infrastructure and add AI/ML capabilities, said the company.

Based in El Segundo, California, Sift was founded by two former SpaceX engineers and they are looking to turn streams of sensor data into actionable insights, as Google Ventures highlighted.

Observability

“At GV, we’re always on the lookout for companies tackling critical challenges in industries undergoing rapid transformation. Sift is doing exactly that for the hardware innovation space,” said Crystal Huang, General Partner at GV.

“Their unified observability platform is the missing piece that leading machine builders need to turn troves of sensor data into actionable insights and accelerate development. We’re excited to partner with the Sift team as they set a new standard for how groundbreaking hardware is developed and operated.”

Essentially, one of sifts founders explains, modern systems – and this relates particularly to space – are becoming too complex for engineers to fully understand.

“The complexity of modern machines has outpaced the tools engineers use to build and operate them, leading to costly delays, preventable failures, and a ceiling on innovation,” said Sift CEO and Co-Founder Karthik Gollapudi. ”

At Sift, our mission is to empower the pioneers building the future by providing them with the first observability platform purpose-built for hardware development. This funding will allow us to accelerate our product roadmap and provide even greater value to our customers as they push the boundaries of what’s possible.”

Sift

Sift describes its platform as “the first unified observability platform for hardware sensor data, empowering engineers to accelerate development, conduct efficient reviews, and ensure reliable operation of complex machines”.

As one of their customers – Astranis Space – puts it, the platform is an “observability stack” for helping automate data review processes, which in turn should increase product reliability.

You can read more about the platform on the company website.

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