In this conversation, Connected World Editorial Director Peggy Smedley gets right to the point asking Twisthink CEO Dave Moelker practical questions about what it really takes to modernize automation. Dave explains how robotics and hardware teams can add secure wireless connectivity to legacy machines, run AI at the edge for high‑speed vision, and turn raw realtime data into predictive insights that prevent downtime.
He doesn’t shy away from the tough issues, mixed‑vendor environments, fragmented data, and the challenge manufacturers face when trying to scale a single automation cell into a full factory rollout. Dave also shares how Twisthink’s human‑centered design approach consistently turns complex telemetry into dashboards frontline teams can actually use.
The result is a clear picture of why Twisthink has become the partner that helps technology providers deliver solutions that can move from isolated pilots to scalable, connected, human‑ready automation.
Connected World: How do you modernize legacy robotics or equipment with secure, wireless connectivity that’s built for today’s digital operations?
DM: We start by understanding what outcome connectivity needs to unlock. Legacy equipment was built to run, not necessarily to talk. If you simply bolt on wireless connectivity without understanding the operator, service model, security posture, and business need, you create complexity without value. We look at the environment, power needs, RF conditions, device identity, data requirements, and workflows. The goal is not to make old equipment feel new. The goal is to make it more visible, serviceable, reliable, and trusted in today’s operations.
CW: Where does edge AI fit into your design platforms, especially for high‑speed vision or sensor workloads that can’t tolerate latency?
DM: Edge AI belongs where time, bandwidth, or reliability make the cloud the wrong first stop. For high-speed vision and sensor workloads, decisions often need to happen at the machine. We use the edge to filter, classify, and act quickly, then send the right data and context to the cloud for broader analysis and learning. It is not edge versus cloud. It is deciding where intelligence creates the most value with the least friction.
CW: Manufacturers are demanding more data from the equipment they buy. How do you help technology providers design solutions that transform raw machine data into predictive insights that prevent downtime and improve throughput?
DM: Raw machine data is not the product. It becomes valuable when it is connected to service history, failure modes, operator behavior, and the actual workflow. We help clients decide what is worth collecting, how to structure it, and who needs to act on it. From there, we design the models, alerts, and workflows that answer practical questions: what is likely to fail, how urgent is it, what should be done, and who needs to know. That is where data starts to drive uptime and throughput.
CW: How do you design products that support the need for unified data and workflows in mixed-vendor manufacturing environments?
Manufacturing environments are rarely clean slate. They are challenging ecosystems of legacy equipment, OEM systems, controls, MES, ERP, maintenance tools, and people with different needs. We design for that reality. That means clear data models, open integration points, role-based workflows, and interfaces that reduce handoffs instead of creating another portal. The win is not forcing every system to be the same. The win is helping the right people move through the work with better context.
CW: How do you simplify complex automation data so frontline teams get dashboards they can act on?
DM: The mistake is thinking more data equals a better dashboard. Frontline teams need fewer, better signals. We start by asking: what decision needs to be made, how fast, and what action follows? Then we design around priorities, exceptions, and plain language. A good dashboard should tell someone where to look, what changed, why it matters, and what to do next. Otherwise, it is just another screen.
CW: How do you help clients balance innovation with cybersecurity, reliability, and regulatory requirements when developing connected industrial products?
DM: We do not see those as separate conversations. Security, reliability, manufacturability, serviceability, and compliance have to be part of the product from the beginning. They cannot be added at the end without creating risk, cost, or rework. That is why we bring hardware, firmware, cloud, UX, and business strategy together early. Innovative products only matter if they can be trusted, supported, certified, and scaled in the real world.
CW: Can you share some stories where you co‑designed hardware and software together to deliver a stronger connected‑product outcome?
DM: A few examples come to mind. For one customer who needed a modernized emissions monitoring platform, the solution was not just a new cloud platform or a new sensing device. It required edge hardware, realtime gas sensing, cellular and Wi-Fi connectivity, AWS cloud services, and a user interface that worked together so teams could monitor emissions at scale.
With Limelight, the value came from combining sensing hardware, wireless control, and mobile and web software. The system had to detect activity, adjust lighting, track energy use, and support maintenance in one seamless experience.
With one of our customers in the trucking industry, the challenge was bringing a backup camera to market. That meant redesigning electronics, improving firmware and code, stabilizing wireless communication, and optimizing the video stream and app experience. In each case, the outcome only worked because hardware and software were designed together from the start.
About the Author
As Twisthink’s CEO, Dave brings a unique blend of technical expertise and strategic leadership to advance what’s possible through connected product development. His roots in RF communications, embedded systems, and signal processing, combined with experience across engineering, product strategy, business development, and operations, allow him to bridge business needs with engineering possibilities to create impactful solutions for clients. Dave can be reached at: davem@twisthink.com