Gather AI: $15M Revenue With Drones and 170% Net Retention - Sankalp Arora
Top Founders
Nathan Latka
4.6 • 702 Ratings
🗓️ 17 June 2026
⏱️ 20 minutes
🧾️ Download transcript
Summary
How do you build a $15M revenue business by teaching autonomous drones to find missing sneakers in warehouses, and get customers to more than double their spend every single year?
Sankalp Arora is the founder and CEO of Gather AI, a physical AI company that uses autonomous drones and computer vision to track inventory in real time across warehouses. He holds a PhD in robotics from Carnegie Mellon, built the world's first safe autonomous helicopter for DARPA, and today has 30 to 40 customers paying an average of $500K per year with net revenue retention of 170%.
You'll learn:
- Why Sankalp spent three years writing code with zero revenue before getting his first customer in 2021
- How a $2 warehouse pick turns into a $15 pick because of one inventory location error, and how Gather cut that by 70% for Barrett
- The land and expand math: customers start with 5 facilities and expand to 100 within three years at $500K per facility network
- Why 170% net revenue retention is possible when your product is embedded in daily warehouse operations
- How Gather AI built neural nets that can read barcodes a standard grocery store scanner cannot, with no human annotation required
- Why Sankalp passed on big-name VCs and chose Smith Point Capital, founded by Keith Block, former CEO of Salesforce
- The forklift vision product that turns any warehouse into an Amazon Go store using off-the-shelf hardware from Best Buy
- How Sankalp was carrying suicidal thoughts since his teenage years and only discovered life without them a year and a half ago, while building a company past $9M in revenue
- The Series B math: $40M raised at roughly $270M to $400M valuation selling 10 to 15% of the business at $15M in revenue
- Why Gather AI is touching just 0.1% of its addressable market today, and what 1% would actually mean in dollar terms
Connect:
YouTube: Nathan Latka
Gather.ai: gather.ai
Founderpath: founderpath.com
Transcript
Click on a timestamp to play from that location
| 0:00.0 | Where are you sort of sitting in this space? |
| 0:02.0 | I think physically AI is at the same point where Chad GPT was in around 2015, where it's just finding its roots. |
| 0:10.4 | What's the average customer may be paying per year? |
| 0:12.5 | Our average deal size is about half a million dollars per year. |
| 0:15.8 | But what is your largest customer pay today on an annual basis, or range is fine? |
| 0:19.5 | I would say about three to four million |
| 0:21.7 | dollars in year. How many individual customers are you working with today? About 30 to 40 logos |
| 0:27.2 | independent customers. Hey folks, my guest today is Sumpkaupora. He is building gather.a. It's a Pittsburgh |
| 0:35.2 | based physical AI company that uses autonomous drones and computer |
| 0:38.7 | vision to deliver real-time inventory intelligence for warehouses, serving a variety of customers |
| 0:43.6 | like Geotis, Axon, and others. He holds a PhD in robotics from Carnegie Mellon University, |
| 0:48.8 | where he built one of the world's first safe autonomous helicopters for DARPA and has raised |
| 0:52.9 | $74 million to date. We'll talk about a series B, which was led by Keith Block Smith Point Capital. SunCop, you ready to take us to the top? Yes, sounds good news. And thank you for having me. All right. Tell us, for folks that are not familiar with sort of the work, you know, NVIDIA is doing on SDKs to, you know, foundation models to program the physical world. Jeff Bezos is, you know, |
| 1:11.0 | reportedly raising a fund to invest in this space as well. Obviously, he's got a lot of warehouses to |
| 1:14.6 | manage. Where are you sort of sitting in this space? Yeah, so I think physical AI, as it's being |
| 1:19.7 | defined today, is robots operating in physical spaces, of course. And historically, the approach |
| 1:27.0 | to that has been to design |
| 1:28.6 | specific autonomy stacks for specific use cases and what the latest and the |
| 1:34.5 | greatest of industries trying to do is build a foundational model much like chat |
| 1:40.2 | gbt that can do anything for text purposes, can do anything for physical spaces. |
| 1:46.0 | And I think if you get an equivalence, I think physically AI is at the same point |
| 1:53.0 | where Chad GBT was in around 2015, where it's just finding its roots. |
... |
Transcript will be available on the free plan in 15 days. Upgrade to see the full transcript now.
Disclaimer: The podcast and artwork embedded on this page are from Nathan Latka, and are the property of its owner and not affiliated with or endorsed by Tapesearch.
Generated transcripts are the property of Nathan Latka and are distributed freely under the Fair Use doctrine. Transcripts generated by Tapesearch are not guaranteed to be accurate.
Copyright © Tapesearch 2026.