With Sift Stack, two former SpaceX engineers are bringing the software that helped launch rockets to the factory floor

Cry “Atoms, not parts!” — a phrase that captures Silicon Valley’s growing obsession with physical manufacturing over digital products — reached fever pitch last week with word that Jeff Bezos is compiling 100 billion dollars Box for roll up and factory automation.

But factory automation is not just a hardware problem. It increasingly relies on sophisticated software and artificial intelligence tools, and this shift is reshaping the companies that build the infrastructure for the world of physical manufacturing.

Karthik Gollapudi, CEO Stack screeningan El Segundo, Calif., company whose tools support the design and manufacture of complex machines like spacecraft and automobiles, feels the Earth shift beneath its feet. He says these changes have reshaped his company’s focus in the past six months.

Gollapudi and his co-founder, CTO Austin Spiegel, started the company in 2022 after working on software tools at SpaceX that managed a massive amount of telemetry data — real-time performance information streaming from sensors on hardware — during testing, manufacturing and launch.

Most companies that build advanced machines use off-the-shelf database tools or create their own Python scripts, but Sift saw the opportunity to provide companies with a best-in-class tool. Clients range from United Launch Alliance, a major US rocket manufacturer, and other defense contractors, to startups in robotics and power grid management.

However, Gollapudi says the arrival of AI tools for data analysis has led to a change in his work. Custom workflows that once stood out as a company’s signature offering are now table stakes in the world of artificial intelligence and deep learning models. But a company’s ability to manage data infrastructure suddenly became more valuable.

“Our long-term vision of how we see this over five years is actually being implemented this year,” Gollapudi told TechCrunch.

This means managing the data-intensive flow of today’s software-intensive devices. Some of the vehicles the company operates contain more than 1.5 million sensors broadcasting data simultaneously, across multiple formats and time scales.

Organizing that data and storing it for AI applications is the company’s goal — “a lot of the value is in making it machine-readable,” Gollapudi said. If AI customers are going to make manufacturing decisions or analyze test data to flag potential problems, Sift’s goal is to make that data available to them.

Good data infrastructure is important for companies like his that might run 10 million automated software tests in a single day, said Jeff Dexter, vice president of software at Astranis, a satellite company that uses Sift to manage test, manufacturing and operations.

“Inevitably, it got to the point where storing data was costing us millions of dollars just a month,” Dexter said. “It’s really like, ‘Is a million dollars well spent?’ With technology like Sift, I don’t have to worry about how much data is out there.”

Gollapudi told TechCrunch that Sift raised a $42 million Series B in 2025 at a post-cash valuation of $274 million, led by StepStone with participation from GV (Google’s venture arm), Riot Ventures, Fika Ventures, and CIV.