News

MassRobotics, the largest independent robotics innovation hub, and Digital Divide Data (DDD), a global leader in human-in-the-loop services for AI and autonomy, today announced a new associated network partnership designed to help robotics companies move faster, smarter, and with greater confidence.

Robotics and autonomous systems depend on accurate data, validated models, and the ability to handle tricky real-world scenarios. DDD brings years of experience providing human-in-the-loop services, such as data annotation, sensor validation, perception training, and edge-case review, that are critical to making robots safer and more reliable. By teaming up with MassRobotics, DDD will support the startups and scaling companies in the MassRobotics community as they bring next-generation robotics to market.

Why This Partnership Matters

• For robotics startups: Access to proven, scalable human-in-the-loop services that can reduce development time and strengthen autonomy performance.

• For DDD: A chance to work side by side with innovators solving the hardest challenges in robotics and autonomy, applying its expertise where it can have the most impact.

Leadership Perspectives

“MassRobotics is thrilled to welcome Digital Divide Data as an Associated Network Partner. Their deep expertise in AI and data operations brings invaluable support to our startup community, helping companies scale smarter and faster. This collaboration strengthens our ecosystem and empowers the next generation of robotics innovators to grow even bigger and bolder.”

 – Colleen Anderson, Director, Community and Events, MassRobotics

“We’re thrilled to partner with MassRobotics and be a value added member of their extended robotics community. Boston is a long-time hotspot for innovation and technology, and we strongly believe that this relationship will let us expand our Data Operations business with more of such advanced tech companies in Physical AI, Robotics and ML-CV space. Much more to come!”

 – Sahil Potnis, VP Product and Partnerships, Digital Divide Data Leadership

About MassRobotics

MassRobotics is the world’s largest independent robotics hub dedicated to accelerating robotics innovation, commercialization and adoption. Our mission is to help create and scale the next generation of successful robotics and Physical AI technology companies by providing entrepreneurs and startups with the workspace, resources, programming and connections they need to develop, prototype, test and commercialize their products and solutions. While MassRobotics originated and is headquartered in Boston, we are reaching and supporting robotics acceleration and adoption globally and are working with startups, academia, industry and governments both domestically and internationally.

About Digital Divide Data

Digital Divide Data (DDD) is a global leader in human-in-the-loop services for AI, robotics, and autonomy. With expertise in data annotation, sensor validation, perception model training, and real-time edge-case intervention, DDD supports leading technology companies in building safe, scalable, and reliable autonomous systems.

Media Contact: Preeti Srivastava (preeti.srivastava@digitaldividedata.com)

Post Event Briefings

Digital Divide Data (DDD) in collaboration with the Pittsburgh Robotics Network (PRN) hosted an evening full of robotics and physical AI conversations in Pittsburgh last month. The event was structured around a panel of experts from different Autonomous Systems’ areas and moderated by Sahil Potnis, VP of Product and Partnerships at DDD. The panel consisted of Al Biglan, Head of Robotics at Gecko Robotics; Barry Rabkin, Director of Marketing at Near Earth Autonomy; Jake Panikulam, CEO at Mainstreet Autonomy and Jeff Johnson, CTO at Mapless AI.

This event was all about how smart machines, like self-driving cars and robots, are starting to show up in everyday life. The term Physical AI just means using artificial intelligence in things that move or do physical work, not just computer programs. These machines are becoming more common in places like factories, warehouses, roads, and homes. As this technology grows, it is important to understand not just how it works, but how it fits into real life and helps people in meaningful ways.

The opening keynote was a message from Sameer Raina, DDD CEO and President, about making sure more people have access to specialized jobs in tech. DDD helps people from underrepresented communities get experience in technology by doing important work, like organizing and labeling data that AI systems use to learn. DDD’s mission is to make sure that the rise of AI creates opportunity for everyone, not just a few. This includes veterans, people from low-income backgrounds, and others who may not normally have a way into the tech world. The panel then talked about what it really takes to go from an idea or a concept to a working commercial product. One of the big takeaways was that trying to build everything yourself can slow you down. It is better to team up with others, focus on what you are best at, and get to the finish line faster and more efficiently. Collaboration is not a weakness, it is a smart strategy to build the right ecosystem.

Another big topic was data. A lot of companies collect more information than they know what to do with. Sometimes they stop tracking things too early, or they toss out data that turns out to be really useful later. When handled the right way, that data can help fix problems, improve safety, and make smarter decisions. In some cases, it can even point to issues that engineers didn’t realize were happening. The panel encourages everyone to think of data as a powerful tool that can make or break a project. The panel also talked about how important it is to think beyond the tech. Just building something cool is not enough. You have to understand who will use it, explain it clearly, and make sure it actually solves a problem. Good planning, strong partnerships, and real communication are just as important as the machine itself.

Looking to the future, everyone agreed that we will see more smart machines all around us. Not to replace people, but to work with them making things easier, safer, and more helpful in daily life. The big message was that for physical AI to succeed, it needs to be useful, trusted, and built with people in mind. With the right mindset, teamwork, and purpose, physical AI can help improve everyday life for all kinds of communities.

The diversity of the panel was very much visible and appreciated by the audience. We ended the evening with a common sentiment of organizing more of such panel talks! Onward to more of such exciting events.

On 10th June, Sahil Potnis, VP of Product and Partnerships at DDD, brought together Autonomy industry leaders for a high-impact roundtable focused on problems autonomous companies are struggling with: collecting meaningful, high-quality data from sensors and cameras.

With around 10 experts at the table, the session started with a refreshingly candid discussion. Sahil pointed out that despite the demand, data collection is still too hard, too expensive, and far too limited for the scale we need to train and validate real-world systems. His perspective resonated with many in the room, setting the tone for collaborative and insightful discussions.

Throughout the session, Sahil emphasized the value of pairing annotated datasets with clearly defined KPIs to drive more focused development and smarter validation. He shared how this approach helps surface performance issues early but also ensures teams are working toward metrics that matter.

The group shared their perspectives on collaboration challenges, use-case gaps, and openly shared issues they’ve encountered in the field. What emerged was a genuine sense of community–people eager to learn from one another and push the industry forward.

Because when it comes to building smarter, safer, more capable systems, better data isn’t optional, it’s everything in the Autonomy industry.

Detroit, MI, USA: Digital Divide Data (DDD) continues to expand its end-to-end data capabilities for Autonomous Systems across land, air, sea, and space. Our latest solution set is targeted towards supporting Autonomous Fleet Operations including Human in the Loop (HiTL) data solutions for:

(A) Remote Teleoperations to enable full Autonomy

(B) Operational Data Intelligence to gather ODD exposure and mission intel insights

(C) Fleet Management functions surrounding the capabilities of mission command and control

(D) In-Cabin Monitoring to drive forward the safety of ADAS systems

“Remote Teleoperations as a Service” is growing rapidly across the globe to augment the core Autonomous premise of any system, and to unlock L3+ and L4 SAE levels of Autonomy. Similarly, using Operational Data Intelligence is an essential part of the fleet operations and is aimed at most effectively deploying assets across multiple sites; be it for testing, or data collection. Cabin Monitoring serves a critical role to directly support any Autonomy company’s CONOPS for safer and reliable operations.

DDD’s in-house expertise on these workflows and ability to stand-up US (onshore) or offshore operations in a lightning quick span of 10 days[1] is a (critical) market differentiating USP necessary to advance the autonomy tech.

“DDD’s Fleet Operation solutions coupled with data operations support services gives our clients the ability to deliver accelerated fleet deployment and management with controlled, scaleable, and cost effective outcomes”, says Sameer Raina, DDD CEO and President.

DDD is actively in pursuit of value-added technology partners to make its Fleet Operations ecosystem robust, scalable and diverse. DDD’s acquisition of Liberty Source PBC in 2024 has supplemented the workforce to have a direct on the ground US presence, vital to unlock low latency – high data security workflows. DDD’s social impact mission, operational excellence of a global workforce (US, Africa, Asia), deep subject matter expertise in Autonomy and toolchain partnerships uniquely positions the team to be an industry leader in providing such end-to-end Autonomy HiTL data solutions.

[1] 10 business days is the average time to set-up a pilot project for an Autonomy focused workflow. Not specific to the Fleet Operations capability.