No-code DataOps + AI for industrial data — energy, utilities, heavy manufacturing.
Active enterprise pipeline (deals)
Industrial AI and DataOps founder; former Global Head of Advanced Analytics at Schlumberger.
LinkedIn ↗“Callapina understood that industrial AI starts with messy operational data, not with demo-ready models. Their perspective helped us frame DeepIQ for customers and investors who care about real deployment timelines.”
Why we backed DeepIQ
Most AI companies in 2024 told a story about the foundation models. DeepIQ told a story about the unglamorous middle: the messy, multi-decade-old SCADA and historian data that runs every refinery, utility, and mine on earth — and the fact that no one had built a no-code DataOps layer that could turn that data into something AI could actually use.
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Why does DeepIQ fit the Callapina thesis?
DeepIQ sits at the intersection of vertical AI and industrial DeepTech: it turns hard-to-use operational data into a deployable AI layer for energy, utilities, and heavy industry.
How does Callapina add value here?
Callapina focuses on three levers beyond capital: market access through US-India customer and partner introductions, fundraising support for the next institutional round, and strategy support around GTM, pricing, positioning, and operating cadence.
Why now?
Industrial customers are under pressure to show AI progress, but their bottleneck is data readiness. DeepIQ attacks that bottleneck directly.
Visit deepiq.com for the company's own story.