India Tech Report

'Where should I put my robots?' This is a question top manufacturing executives at some of the biggest industrial complexes around the world are asking, says Saurabh Chandra, founder and CEO at Ati Motors, a Bengaluru robotics venture that makes autonomous mobile robots for factories.Data holds the key to unlocking this solution, and often while manufacturers have a good intuitive view of what's happening, they don't yet have a quantified view, clearly based on data, of their factory processes, he says.Here's two minutes on how Ati is helping its customers change this scenario, with its AI-led materials movement orchestration platform. You can catch the full conversation with Saurabh via the related post link.

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In this episode, I catch up with Saurabh Chandra, founder and CEO at Ati Motors, to discuss his views on how factory automation is evolving in the era of physical AI, as robots finally begin to “break out of the yellow cages” of safety zones.

Ati Motors makes autonomous mobile robots for materials movement in factories, and its customers include several Fortune 500 companies. As Ati expands its footprint into the US market, Saurabh outlines a future where Physical AI and software agents work in tandem to redefine the “Digital Assembly Line.”

The idea of a “lights out” factory or a “dark factory” is decades old. Engineers dreamed of fully automated installations where robots and machines took over — without human intervention — and made useful things for us. Cars, for example.

But a combination of both technical challenges and real-world non-engineering problems ensured that such factories remained more science fiction and less reality. Until recently. Today, many experts in the industry and advanced manufacturing believe that we’re approaching a tipping point with respect to automation and robotics technologies.

In this conversation, Saurabh outlines the idea of an AI-led materials movement orchestration platform that Ati has already deployed with some early customers. The idea is that factory executives are beginning to realize that the real value on the shop floor isn’t the robot itself, but the material it moves.

Saurabh explains why traditional ERP systems often fail to track Work-in-Progress (WIP) inventory, leaving a visibility problem as SKU complexity has multiplied manifold over the last 15 years. By creating a “spatial system of record” that tracks every trolley, bin, and staging area in real-time, Ati Motors is helping global giants move from intuitive management to quantified, data-driven orchestration.

Global manufacturing is currently caught in a pincer movement of structural labour shortages across advanced economies and a geopolitical push to reshore production closer to end consumers. As the “factory of the world” model decentralises away from China, the future of Western industrial hubs depends on their ability to integrate “physical AI” that can handle the hyper-personalised, high-SKU demands of modern commerce.

This manufacturing arms race, increasingly prioritized by the boards of Fortune 500 companies, is turning autonomous orchestration from an experimental project into the essential infrastructure of 21st-century industrial sovereignty.

“A lot of people in large companies, for whom status quo was their friend, find that situation is now absolutely in the past,” Saurabh notes during the interview. And at Ati, “we have really transformed into an organization where the robots are the means to the end, which is finally making sure that the factory runs in the way it’s supposed to. The goal is to create a system of record for the shop floor — integrating physical agents, software agents, and humans into a single, intelligent orchestration layer.”

The platform, Ati Flow, also considers how physical AI or robots, software AI agents and humans will all interact making factories of the future more efficient and sustainable. And Saurabh gives us a sense of how the journey to the dark factory will likely involve three phases and how he thinks Ati can catalyse and facilitate that transformation.

Chapters

(01:24) The evolution of Physical AI and the future factory

(03:43) Market traction and the new urgency for AI agents

(07:44) Manufacturing vs. warehousing: the complexity of making things 

(11:35) The 10X SKU problem and the latent demand for data 

(17:23) From Robot vendor to material orchestration platform

(22:05) Real-world RoI: reconciling inventory and reducing assembly line starvation

(30:50) The three-phase roadmap to the dark factory

(35:35) Specialization vs. mimicry: breaking the “Yellow Box” metaphor

(43:28) Global manufacturing 2030: the democratisation of gigafactories

The idea of a “lights out” factory or a “dark factory” is decades old. Engineers dreamed of fully automated installations where robots and machines took over — without human intervention — and made useful things for us. Cars, for example.

But a combination of both technical challenges and real-world non-engineering problems ensured that such factories remained more science fiction and less reality. Until recently. Today, many experts in industry and advanced manufacturing believe that we’re approaching an “inflection point” — yes, that cliche, but it might be true — with respect to automation and robotics technologies.

Saurabh Chandra, founder and CEO at Ati Motors, discussed his views on some of these points with me earlier this week. Ati makes autonomous mobile robots for materials movement in factories, and it’s customers include several Fortune 500 companies.

Saurabh spoke about how Ati is preparing for the “Future Factory” where robots will no longer stay in the safety zones of “yellow cages” but mix with humans and other robots. He outlined the idea of a materials (and robots and even human) movement orchestration, which Ati has already developed an early platform for, envisioning the physical AI, software AI agents and humans all interacting with one another in making factories more efficient and sustainable.

Catch the full conversation right here on Friday, April 10, or wherever you get your podcasts. Here’s a one-minute preview, with Saurabh explaining how we’ll rendezvous with robots.

In any field, and especially in deep tech, India's startups don't get the type of funding that Silicon Valley ventures command. In fact even a modest Series A fund raise takes a long time and represents a solid achievement for Indian startups.

Therefore how can they make a dent, globally, in a field like robotics that is extremely hardware intensive and integrating the physical robot and its "intelligence" is a daunting task. Especially for any entrepreneurs looking to build humanoids.

In a recent conversation with me, Arjun Dutt, a partner at Bain & Company, and a former tech entrepreneur himself, offered his views on what and how Indian robotics startups can do to strategically position themselves.

You can find the full conversation via the related post link below. Here's two minutes on the four priorities that Arjun suggests: "going narrow," taking hybrid approaches to the form factor, building partnerships, and offering the best technical solutions to specific layers of the tech stack that currently are universal pain points that everyone in the field is dealing with.

The ultimate aim for robot makers is to build a fully general-purpose machine that can pretty much perform any task that we can do. At that point we'll have robots that can finally relieve us of the daily drudgery of doing the laundry, washing the dishes and putting out the trash.
In the mean time, there are two distinct approaches being followed by robotics companies, says Arjun Dutt, a partner at Bain & Company, who recently discussed the global consultancy's views on how these technologies are evolving and what's influencing their deployment.
The first is to look at specific tasks, like those repeatedly needed in factories and warehouses, for example, and build robots that can takeover — part of the attraction here is the labour shortage in the advanced economies. This isn't generally an issue in the global south, where labour is available but skilled labour requires training at scale.
The second approach is far more ambitious, because it's about solving general robotic intelligence and capabilities in unconstrained settings, Arjun points out. Arjun is a former tech entrepreneur himself. He is an electrical and computer engineer by training and a specialist in commercial applications of AI technologies.
Catch the full conversation via the related video link. Here's two minutes on Arjun's viewpoint, explaining the two divergent approaches briefly.

Arjun Dutt, a partner at Bain & Company, spoke with me a couple of weeks ago on the global consultancy's views on how robotics technologies are evolving.

Arjun recently co-authored a note on the impact of early commercialisation of humanoid robots — how that will likely play out in three waves, from 'brownfield' plants to eventually, our homes.
You can catch the full conversation via the related post below. Here's a short chapter with Arjun briefly explaining the four critical areas in which advancements are needed before humanoids can be more human-like.

And one technology might be holding back even faster adoption of these robots. It might surprise you to know that it's not intelligence.

In this episode, we explore the rapidly evolving world of physical intelligence with Arjun Dutt, a Partner at Bain & Company and former entrepreneur. As generative AI transitions from digital interfaces into the physical world, Arjun explains why humanoid robots are emerging as a solution to the worsening labour shortages, especially in the so-called ‘brownfield’ plants in many advanced economies.

We dive into Bain’s four-point definition of humanoids — adaptive intelligence, spatial perception, bipedal dexterity, and sustained power — and talk about how the current battery technologies remain the “long pole in the tent” for true autonomy.

Arjun outlines the three waves of adoption that are discussed in a recent note that he co-authored, predicting that while industrial brownfield settings will see scale within three to five years, consumer-centric home robots are at least a decade away.

You will also find interesting insights on the following topics: The role of generative AI as a “foundational capability,” allowing robots to learn via observation and training data rather than rigid, scenario-based programming; the evolution of specific task-oriented robots versus truly general-purpose humanoids; and where might the eventual “control points” lie, as Arjun put it, of humanoid robots – meaning, who’ll control the most critical technologies in these robots?

Lastly, we touched upon his advice for India’s deep tech entrepreneurs, discussing the merits of “going narrow” and how to navigate the reliability and regulatory hurdles of the US market.

Chapters

(00:55) Introduction to Arjun Dutt and the rise of physical intelligence

(04:40) Why generative AI makes the shift to physical automation feel inevitable

(06:16) Defining the four pillars of a modern humanoid robot

(08:42) Generative AI as a foundational capability for robotic learning

(11:33) Addressing global labor shortages through brownfield automation

(15:26) Understanding the three waves of humanoid adoption

(18:40) Expected timelines for industrial, professional, and home robotics

(23:21) Why battery technology remains the long pole in the tent

(28:38) Current pilot use cases from automotive plants to warehouses

(34:10) Choosing between task-specific and general-purpose strategies

(37:07) Navigating human factors and the complex regulatory landscape

(43:24) Strategic advice for Indian deep tech entrepreneurs

Coming up on India Tech Report, we dive into the future of physical intelligence with Arjun Dutt, Partner at Bain & Company. Arjun explains how, aided by both physical tech breakthroughs and generative AI moving beyond the screen and into the physical world, humanoid robots are on the cusp of becoming a likely solution to global labor shortages – one of the big applications driving the multi-billion-dollar investments into this form factor.

We explore Bain’s four-pillar definition of a humanoid — intelligence, perception, dexterity, and sustained power — and why current battery technology remains the “long pole in the tent” for true autonomy.

Arjun breaks down the “three waves of adoption” of humanoids that he and his colleagues Xin Cheng, Anne Hoecker and Peter Hanbury outlined in a recent note: starting with industrial brownfield settings – massive sunk investments with infrastructure built around how humans work – in the next three to five years, moving to mining and construction by 2030, and finally reaching consumers’ homes as early as within a decade.

For the builders out there, Arjun draws on his own entrepreneurial roots to offer his insights for Indian robotics startups navigating the global stage. Should you build the full stack or “go narrow”? How do you scale manufacturing and reliability for the US market? From the state of the art in robot training to the regulatory hurdles ahead, this is a quick look at the race to build a general-purpose worker.

Catch the full conversation on Tuesday, March 17th right here, or wherever you get your podcasts. Here's a 90-second preview with Arjun explaining the connection between generative AI and robotics.

Once upon a time, it used to be a popular joke in many industry speeches in India — one that government leaders used to sportively join in — that the IT services industry grew “despite the government.” Of course, it was untrue. Several forward-thinking officials and technocrats in governments both at the central and state levels played a strong role in helping that industry grow. As did many top political leaders.

Today, with deep tech, while micro-procedural frustrations still very much remain, no one needs to say they need to grow despite the government. Public support is visible and hundreds of thousands of crores of rupees are being committed in mission mode to R&D and Innovation.

In a recent conversation with India Tech Report, Gokul NA, founder of CynLr, a robotics venture based in Bengaluru, spoke about the other side of the table — those representing private industry, and what they need to do if India’s deep tech ventures are to have a serious chance in the long term.

Catch the full conversation by clicking on the the related post link below. Here’s two minutes on the need for exporting “homegrown IP,” building world-class research clusters and more.

In today’s episode, we dive into the future of robotics with Gokul NA, founder of CynLr, or Cybernetics Laboratory, perhaps one of India’s most advanced companies in this field.

CynLr is headquartered in Bengaluru, with an advanced R&D Lab in Switzerland and a growing customer-facing operation in the US, where Gokul’s fellow founder Nikhil Ramaswamy is based.

The entrepreneur duo and its 85-member team are tackling a challenge that scientists and engineers have been working on for several decades: the ability for robots to intuitively handle unfamiliar objects without custom programming or prior training.

In this conversation, Gokul explains their new “Object Intelligence Stack,” a system designed to imitate some of the functions related how a human brain might learn — much like a baby impulsively grasping a new toy without knowing its name or purpose.

By collaborating with the Centre for Neuroscience at the Indian Institute of Science, CynLr is translating brain-function research into a sophisticated software and sensor framework. Shifting the focus from algorithms that work on data to the “physics of objects,” CynLr’s intelligence stack is what Gokul describes as the precursor to a “manipulation OS.”

Drawing parallels to Apple in the 1980s, Gokul shares his vision for a future of “object computers” and micro-factories – important components of CynLr’s vision for global manufacturing, where instead of Giga-factories, we might have fabrication facilities as small as a car dealership or even a garage.

Chapters

(00:00) Challenges of building a deep tech organization in an absent industry

(05:58) Imitating the human brain’s ability to handle unfamiliar objects

(09:18) Partnering with neuroscience researchers to replicate human intuition

(11:32) Developing a manipulation operating system and the future object store

(19:47) Automating assembly for automotive and semiconductor manufacturing

(25:17) Transitioning from rigid gigafactories to software-defined micro-factories

(35:49) Fostering a deep tech ecosystem to address the brain drain

(40:18) Strategic funding goals and the technical roadmap for scaling

Gokul and Nikhil are backed by investors including Speciale Invest, growX ventures, Pavestone VC, Athera Venture Partners (formerly Inventus India), Anicut Capital, Arali Ventures, Redstart Labs, and several other institutional and angel investors.

CynLr’s long-term vision also involves creating a manipulation operating system and an “object store” and a “task store” to transform flexible manufacturing, just as the App Store transformed the smartphone.

Currently, they are deploying these solutions in the automotive and semiconductor industries to automate some complex manual assembly processes.

In this conversation, Gokul also talks about some of the challenges of building a company like CynLr in India, where many important ingredients are missing, and what he thinks the industry can do to change that.