He Raised $74 Million To Bring Real-Time Intelligence to Warehouses With AI-Powered Vision

AI and robotics are having a moment. But very few founders are actually building at the intersection of deep tech, real-world deployment, and scalable business models. Gather AI CEO & co-founder Sankalp Arora, PhD, is one of them.

From growing up in Delhi with a childhood obsession with robots to building one of the most advanced warehouse-intelligence platforms in the world, Sankalp’s journey is a masterclass in conviction, technical depth, and execution under pressure.

This is the story of how curiosity turned into company-building—and how robotics is quietly reshaping global supply chains. In a riveting conversation on the Dealmakers Podcast, Sankalp talks about getting into Carnegie Mellon without spending a dime and receiving awards from media outlets.

Listen to the full podcast episode and review the transcript here.

A Childhood Wired for Robotics

Sankalp didn’t “discover” robotics later in life. He was wired for it. Growing up in Delhi in a joint family, surrounded by cousins, cricket, soccer, and academics, he was always drawn to one thing: building machines that move and think.

“Since I was 5 years old and can remember, I just wanted to make things that move, that can think,” Sankalp recalls. For many in India, engineering is a default path. For him, it was something deeper—it was instinct, “a very natural proclivity, just a neural network being wired like that,” he remarks.

After doing his undergrad at Delhi College of Engineering, Sankalp continued building small robots with limited resources. But he knew that to truly push boundaries, he needed to be in the best space possible. That meant one place–Carnegie Mellon University (CMU).

During his undergrad studies, Sankalp had worked on India’s first truly autonomous tank. One of the people he had worked with referred him to a professor at CMU.

Betting Everything on Carnegie Mellon

Carnegie Mellon University is widely regarded as the epicenter of robotics innovation. It would have a pivotal role in Sankalp’s life. He would go on to get every degree possible from the university, which is in itself a spectacular feat.

However, getting in is hard. Affording it is even harder. Sankalp didn’t have the financial means—but he had something more valuable: proximity to opportunity. Through a connection, he reached out to Professor Sanjiv Singh and struck an unconventional deal.

If he proved himself within three months, Professor Singh would give Sankalp a staff position, which would fund his education. Sankalp’s father had to take a loan just to pay for the flight ticket to the US. But three months later, the bet paid off.

Sankalp earned the position, and his master’s and PhD were fully funded through the lab and the Department of Defense. While at CMU, he worked on groundbreaking projects—including the world’s first fully autonomous helicopter. But one idea stood out.

The Core Insight: Make Robots Curious

During his PhD, Sankalp focused on a fundamental question: How do you make robots curious in physical environments?

This wasn’t just academic; it became the foundation of what would later become Gather AI, which uses autonomous devices and AI-equipped cameras to monitor operations across warehouses.

Toward the end of his PhD, Sankalp realized that the most direct way to have a positive impact on the community through his inventions was entrepreneurship. Founding companies would actually enable him to meet the people whose lives his inventions would benefit.

By this time, Sankalp had published a few papers that focused on making robots autonomous using only cameras. These papers had attracted interest from some of the world’s largest autonomy companies to license the technology. The timing was perfect to test the impact in real-life spaces.

Considering this was his first job ever, Sankalp had a lot to learn. Although he had a deep knowledge of the robot autonomy and the curious robots domain and space, he knew very little about the outside world. Thus, he signed up for VentureBridge, an innovation fellow and CMU incubation program.

As part of this program, Sankalp received funding from the Department of Defense for customer discovery.

Finding the Right Problem: 175 Conversations Later

Great founders don’t just build technology—they match it to urgent problems. Using the funding, Sankalp and his team conducted 175 customer discovery interviews. As he recalls, they had the “hammer” (cutting-edge robotics + AI). Now, they needed the right “nail.”

Sankalp and his team found it in supply chains and supply chain visibility. They realized that if they could make curious robots for operations within the four walls of a warehouse, it would solve an urgent need. They could address a large enough market and have a global impact.

This is where their core thesis of using AI to gather data comes in. As Sankalp reveals, the fascinating part was that other companies, including YC-funded ones, had tried this before and failed to materialize the technologyas intended.

When Investors Said “This Isn’t Possible”

The early fundraising story is a classic deep-tech paradox. The tech was groundbreaking, which made investors skeptical. The default response Sankalp heard: “This doesn’t work.” So he did something unconventional. He brought the product to the investors.

Sankalp built mock warehouses in Salesforce Tower offices and flew drones during pitch meetings to demonstrate the technology in real time. At the same time, he secured early customer validation: “If you build it, I’ll buy it,” they said.

These customers had full faith in the tech stack and the tech ability. That combination—live proof + customer pull—unlocked the first funding. This was sometime in 2019.

What Gather AI Actually Does

At its core, Gather AI turns ordinary cameras and hardware into intelligent data collectors. As Sankalp explains, they can use the most basic hardware available at Best Buy, whether for drones or forklift-mounted cameras. Next, they digitize workflows and inventory data in warehouses using cameras.

By digitizing those workflows, Sankalp and his team offer not just real-time visibility but also enable warehouses to ship more goods on time and fulfill orders in full. At the same time, they are reducing the amount of labor they spend on shipping each and every item.

From the customer’s perspective, all they need to do is click on a product on an e-commerce site and have it magically appear at their doorstep. Gather AI provides the backend technology that makes the magic happen—as promised by the e-commerce vendor.

The First Signal of Product-Market Fit

Sankalp realized that Gather AI had built the world’s first such technology. No other team or tech stack can take a camera and transform it into an effective data-gathering tool using just software. He had immense faith in his team’s tech capabilities.

Before scaling, there was a clear moment of validation. After launching a basic website—with zero outbound effort—Gather AI generated $5M in pipeline within a month. That told Sankalp two things. One is product market fit, and the other is the core technology.

People were reaching out to Gather AI, affirming they needed a solution to their problem. It still took three years to fully develop the technology. But when it was ready, customers didn’t just adopt it—they expanded rapidly across multiple facilities and have continued to grow their footprint.

As Sankalp points out, landing customers was relatively easy because the problem was easy to solve. Next, they started scaling the solution rapidly—both were distinct checkpoints in the product-market footprint.

Raising $74M—and the Power of the Right Investors

To date, Gather AI has raised $74M across multiple rounds. Sankalp reveals that they first raised a pre-seed round of ~$3M, and then, a seed round worth $10M led by Expa and Xplorer Capital. He considers himself fortunate to receive support from top mentors and credible people.

For instance, Expa is a startup studio and venture fund founded by Garrett Camp, who is known as the co-founder and first CEO of Uber. Xplorer Capital was founded by serial entrepreneurs who have sold multiple companies to Amazon. Kiva Robotics is one of them.

Gather AI’s further growth rounds included $10M from Tribeca Venture Partners, $17M from Bain Capital Ventures, and $40M Series B from Smith Point Capital (cofounded by Keith Block, the ex-CEO of Salesforce).

These investors weren’t just funding the company—they were reinforcing conviction.

Storytelling is everything that Sankalp was able to master. The key is capturing the essence of what you are doing in 15 to 20 slides. For a winning deck, take a look at the pitch deck template created by Peter Thiel, Silicon Valley legend (see it here), where the most critical slides are highlighted.

Remember to unlock the pitch deck template that founders worldwide are using to raise millions below.

The Near-Death Moment: COVID

Right before COVID hit, Gather AI was about to sign a major multi-facility deal with one of the top global retailers. Six months of negotiations had resulted in a verbal confirmation on Friday that the final signatures were expected on Monday.

Sankalp and his team were looking forward to the significant revenue they were expecting to earn from the deal. That just disappeared. Further, all the warehouses in the US shut down to external vendors and partners as they figured out how to operate on their own.

For the next six months, no one was allowed to be in any of the warehouses. As Sankalp sees it, the challenge of surviving centered on having no new leads for those six months. But talking to people in warehouses made him realize the trust and conviction Gather AI had earned.

Investors and current employees continued to invest in Gather AI. They were confident that when things opened—and they would eventually open—they would find enough business, which did happen because Gather was solving a relevant problem.

When warehouses reopened, demand surged—and Gather AI was ready. Sankalp talks about how their conviction was really tested, as all they could do was double down on product and engineering despite having no sales at all.

The Bigger Vision: Fixing the Global Supply Chain

As Sankalp points out, most consumers may not understand the real impact or experience much change other than receiving deliveries on time. Though instead of same-day delivery, they can now expect deliveries within a couple of hours.

But for the people working in the warehouses, efficiency means not having to run around the warehouse looking for lost items. It means they can go home much earlier to their kids.

Today, inefficiencies in supply chains cost companies billions. Retailers often hold 5% to 15% of annual revenue in inventory. For a $5B company, that’s up to $750M sitting idle—around $0.5B worth of extra inventory in warehouses, depending on how logistics are operating.

Gather AI’s vision is to eliminate this inefficiency. In a fully realized future, Sankalp sees this kind of technology helping to protect supply chain surprises arising from geopolitical factors, such as the pandemic. Supply chains become resilient to disruptions, and warehouses operate with real-time intelligence.

Who Wins: AI vs Robotics?

Sankalp has a nuanced view of the AI landscape. His eight years as an entrepreneur have taught him that the people who will win are the people who deliver value and own the workflow.

In most desk jobs, workflows are owned by large language models (LLMs), not physical AI. Any white-collar work is mostly catered to and owned by large language model-driven workflows. Or it can be something in the digital domain, unless a better architecture than the current transformer emerges.

In Sankalp’s perspective, physical AI is still quite young because the core principles stay the same. As a result, in white-collar work, LLMs can be closely monitored and supervised. Any ramifications can be dealt with, and errors can be quickly corrected.

But in physical environments, the tolerance to mistakes is much lower. The consequences are much more serious in cases involving robot-related injuries or the endangerment of human life.

As a result, a longer tail is needed—much like autonomous cars, which are the first large-scale physical AI humans are fielding.

But eventually, most of the actions we perform manually or move around will be taken over by robots. Sankalp anticipates that these tasks will be taken over by humanoid robots.

Specific solutions that optimize the efficiency of particular workflows industries need will likely emerge. Physical AI could be a humanoid butler at home, where, beyond efficiency, people care about flexibility. Even then, large language models will always be needed.

As Sankalp underscores, large language models can win on their own simply because they can take over white-collar work and automation. Winning without large language models will be challenging.

Building a Team of 75 Around One Principle

At Gather AI, hiring isn’t just about technical excellence. Two traits matter more than hiring the best in their domain in the world—people who are the best in building physical AI that actually works in the real world and not just in a compute cluster.

• Customer Compassion: People who deeply understand and care about the problem and how it can help someone’s life. As a result, Gather AI has attracted employees who have experienced this problem themselves or in some form at work. For instance, people from large supply chain companies like Amazon, Walmart, and Uber, as well as other deep tech companies. Yet another example is people from autonomous car companies with an ecosystem in Pittsburgh.
• High Agency + Curiosity: People who take ownership and explore beyond their domain. Interviews at Gather AI are designed to filter and identify such talent. That’s how Sankalp has recruited the 75+ people at Gather AI. They are a group of people who are really driven to solve someone’s problem and take ownership of it. They are curious about building because building a product like Gather AI takes full-stack machine learning, autonomy, mobile development, customer success, solutions, and sales—all working together across the board.

Lessons for Founders

Looking back, Sankalp highlights three key lessons:

• If the mission is right, people will align with you and join you in the journey: Early doubt about attracting talent is natural—but conviction compounds. As Sankalp has worked most of the time independently, he believes in owning his thesis, even if a large team contributes to it.
• Hire carefully early on: Early hires shape culture and trajectory. It was hard for Sankalp to predict how people would join his journey and if they would have the same dedication and curiosity to solve customer problems. He believes in carefully vetting hires and getting to know them up front.
• Deploy capital aggressively: “Investor money is not meant to sit in the bank.” Being too conservative early on costs momentum.

Final Thought: Curiosity as a Competitive Advantage

Sankalp’s journey—from a kid in Delhi dreaming about robots to building a category-defining company—comes down to one trait: curiosity, and not just in machines. But in order to understand problems deeply, challenge assumptions, and push boundaries in the real world.

In a world flooded with AI hype, the companies that win won’t just build models; they’ll build systems that work in the real world. And that’s exactly what Gather AI is doing.

Listen to the full podcast episode to know more, including:

• Curiosity compounds into company-building when paired with the selection of real-world problems.
• Deep tech only works when it translates into clear, measurable customer value.
• 175 customer conversations beat assumptions every time in finding product-market fit.
• Proof in the real world converts skeptics faster than any pitch deck ever will.
• Strong pipeline pull is the clearest early signal that a problem is worth solving.
• Conviction during zero-revenue periods is what separates survivors from casualties.
• Winners in AI will be those who own workflows, not just build technology.

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Keep in mind that storytelling is everything in fundraising. In this regard, for a winning pitch deck to help you, take a look at the template created by Peter Thiel, the Silicon Valley legend (see it here), which I recently covered. Thiel was the first angel investor in Facebook with a $500K check that turned into more than $1 billion in cash. 

Remember to unlock for free the pitch deck template that founders worldwide are using to raise millions below.

 

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