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[Funding News] CA-based Sift Raises $17.5M Series A Funding to Propel the Future of Machine Innovation

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Today marks an exciting milestone for Sift as Sift announce $17.5M Series A funding round led by GV (formerly Google Ventures). This funding, which brings our total capital raised to $25M, is a testament to the growing need for unified observability in complex machine development.
Today marks an exciting milestone for Sift as Sift announce $17.5M Series A funding round led by GV (formerly Google Ventures). This funding, which brings our total capital raised to $25M, is a testament to the growing need for unified observability in complex machine development.
Today marks an exciting milestone for Sift as Sift announce $17.5M Series A funding round led by GV (formerly Google Ventures). This funding, which brings our total capital raised to $25M, is a testament to the growing need for unified observability in complex machine development.

Today marks an exciting milestone for Sift as Sift announce $17.5M Series A funding round led by GV (formerly Google Ventures). This funding, which brings our total capital raised to $25M, is a testament to the growing need for unified observability in complex machine development.

Read also – [Funding News] UT-based Route Raises $40M Series C Funding

Sift thrilled to have GV’s support and expertise as accelerate mission to empower the pioneers building tomorrow’s groundbreaking machines.With our Series A funding, we’re poised to accelerate product vision and expand our ability to serve customers across the full hardware development lifecycle.

Read also – [Funding News] Bright Machines Raises $126M Series C Funding to Propel Manufacturing Into Software-Defined Era

“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 GV General Partner Crystal Huang, “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.”

Despite the high stakes, hardware teams today lack the tools to effectively manage the floods of sensor data generated by their complex machines. Engineers are forced to stitch together ad hoc in-house solutions or juggle an array of limited point solutions across disparate teams. This fragmented approach leaves critical gaps in data visibility, hindering collaboration and slowing innovation.

Sift is already the backbone for mission-critical machines at pioneering companies like K2 Space, Astranis, True Anomaly, Astrolab, MACH, Parallel Systems, and many more. Jeff Dexter, Sr. Director of Software at Astranis Space, shared “with Sift’s advanced observability stack, we’re automating much of the manual data review process to increase reliability while accelerating development. Their platform will be a critical tool in our mission to deliver reliable, cost-effective internet to those who need it most.”

For Parallel Systems, choosing Sift was a crucial decision. Kevin Limburg, Manager of Validation and Fleet Software explained that “With so much riding on these machines, every engineer diverted to fixing our dated telemetry system feels like lost momentum. We needed a modern solution to help move us forward.”

Sift envision a future where the barrier to world-changing hardware innovation isn’t sensor data wrangling, but the limits of human ingenuity itself. Today’s funding announcement is an exciting step towards realizing that future, but it’s still just the beginning. We’re beyond grateful for the support of our investors, the trust of our customers, and the dedication of our team. Together, we’ll continue building the most robust software for hardware companies — and enabling the next great leaps in machine innovation.

About Sift

Founded in 2022, Sift is the first unified observability platform for hardware sensor data. Its stack brings everything into one place, delivering powerful real-time insights that engineers need to accelerate development, conduct efficient reviews, and ensure the reliable operation of their machines.

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