India Tech Report

Tag: robotics

  • Eka Robotics bets on force, not language, to teach robots dexterity

    Eka Robotics bets on force, not language, to teach robots dexterity

    Eka Robotics has emerged from stealth with a Vision-Force-Action model that it says can push robots beyond the long-standing trade-off between generality and speed in manipulation tasks. The Cambridge, Massachusetts startup was co-founded in 2025 by MIT’s Pulkit Agrawal and former DeepMind researcher Tuomas Haarnoja. The deep tech entrepreneurs are pitching force sensing and simulation as the route to more capable machines.

    In robotics, much of the recent excitement has centred on vision-language-action systems, which treat language as a bridge to physical control. Eka says that is too indirect for the contact-rich realities of the physical world. Its approach instead tries to make robots learn mass, friction and inertia through practice in high-fidelity simulation, then transfer those skills to the messier settings of factories and homes.

    Across the robotics industry, the race is on to build foundation models that can scale across tasks, rather than brittle systems tuned for one environment, and the prize is a larger share of warehouse work, light manufacturing and household assistance. The strategic question is whether the winning path is imitation from human data, reinforcement learning in the real world, or simulation-first training that seeks to compress years of trial and error into computational time.

    “We’re building intelligence for the physical world in its native language: forces,” Pulkit Agrawal wrote on LinkedIn. In the same post, he added that robotics has long faced a trade-off between “generality” and “speed,” and that “the real world requires both”.

    Eka’s presentation suggests confidence that force-aware control can do more than sort objects or pick up toys. The company has highlighted tasks such as screwing in a light bulb and handling slippery items, small feats that still define the frontier of robotic manipulation. For now, the message is as important as the model: the next leap in robotics, Eka is arguing, will come not from making machines more verbal, but from making them more physical.

  • ‘Where should I put my robots?’ Saurabh Chandra at Ati Motors offers his views

    ‘Where should I put my robots?’ Saurabh Chandra at Ati Motors offers his views

    ‘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 below.

  • Saurabh Chandra on ‘future factory’ vision in era of physical AI

    Saurabh Chandra on ‘future factory’ vision in era of physical AI

    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.

  • Coming up: Saurabh Chandra at Ati Motors on a rendezvous with robots

    Coming up: Saurabh Chandra at Ati Motors on a rendezvous with robots

    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.

  • Four ways India’s robotics startups can win

    Four ways India’s robotics startups can win

    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.

  • Humanoid robots: which approach will win the race?

    Humanoid robots: which approach will win the race?

    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.