The rallying cry of “atoms, not bits!” — a phrase encapsulating Silicon Valley’s escalating focus on tangible manufacturing over purely digital innovations — reached a peak recently with the announcement of Jeff Bezos’s ambitious $100 billion fund dedicated to acquiring and automating factories.
However, the automation of manufacturing facilities is no longer solely a hardware challenge. It increasingly relies on sophisticated software and advanced AI tools, a paradigm shift that is fundamentally reshaping the companies responsible for building the foundational infrastructure of the physical manufacturing sector.
Karthik Gollapudi, CEO of Sift Stack, an El Segundo, California-based firm specializing in tools that facilitate the design and production of intricate machinery like spacecraft and automobiles, is keenly observing this evolving landscape. He notes that these industry shifts have profoundly influenced his company’s strategic direction over the past six months.
Gollapudi, alongside his co-founder and CTO Austin Spiegel, established Sift Stack in 2022. Their venture stemmed from their prior work at SpaceX, where they developed software solutions to manage the immense volumes of telemetry data — real-time performance information streamed from sensors on physical components — generated during testing, manufacturing, and launch phases.
While most companies engaged in building advanced machines typically resort to off-the-shelf database solutions or custom Python scripts, Sift Stack identified a crucial market opportunity to deliver a superior, best-in-class tool. Their diverse client base now includes prominent entities such as United Launch Alliance, a leading U.S. rocket manufacturer, various defense contractors, as well as innovative startups in robotics and power grid management.
Yet, Gollapudi explains that the emergence of AI tools for data analysis necessitated a significant strategic pivot for his business. The bespoke workflows that once distinguished Sift Stack’s offerings have rapidly become standard expectations in an environment dominated by AI and deep learning models. Consequently, the company’s core expertise in managing robust data infrastructure unexpectedly surged in value.
“Our long-term vision of how we saw this playing out over five years is actually being played out this year,” Gollapudi shared with TechCrunch, highlighting the accelerated pace of industry transformation.
This acceleration translates into the critical task of managing the intense data streams originating from today’s software-intensive machines. Some of the vehicles Sift Stack works with are equipped with over 1.5 million sensors, all concurrently streaming data across a multitude of formats and time scales.
The company’s primary objective is to organize and store this vast data specifically for AI applications. “A lot of the value is in exposing that to be machine readable,” Gollapudi emphasized. Sift Stack aims to make this data readily accessible to AI agents, enabling them to make informed decisions about manufacturing processes or analyze test data to proactively identify potential issues.
Jeff Dexter, VP of software at Astranis, a satellite company that leverages Sift Stack for managing its testing, manufacturing, and operational data, underscored the importance of robust data infrastructure. He noted that it is vital for companies like his, which might conduct as many as 10 million automated software tests in a single day.
“Inevitably, it gets to a point where it’s costing us millions of dollars per month just to store data,” Dexter stated. He added, “It’s really like, is this a million dollars well spent? With technology like Sift, I don’t worry about how much data is there.”
Gollapudi also informed TechCrunch that Sift Stack successfully secured a $42 million Series B funding round in 2025, achieving a post-money valuation of $274 million. The round was led by StepStone, with additional participation from GV (Google’s venture arm), Riot Ventures, Fika Ventures, and CIV.
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