FAQs

You can, but it’s risky. Think of it like building a house without a blueprint. You save time and resources upfront, but you’ll likely pay double later to fix structural mistakes. Discovery is your insurance policy.

Usually about two weeks, start to finish. That includes the pre-work analysis, the 1-2 day intensive workshop, and a few days for us to finalize the strategy roadmap. However, this timeline can shorten or expand based on the complexity of your business challenge and the solution needed for that.

Keep it small but critical: A Decision Maker (for budget), a Subject Matter Expert (for deep knowledge), and a Product Owner. If there are technical constraints, bring your Lead Developer.

Yes. An RFP is a wish list; Discovery is a reality check. We use this time to challenge assumptions and ensure your requirements actually solve the business problem before we start billing for development.

For some, yes. Technologies like Cloud Robotics and massive IIoT deployments depend heavily on the low latency and high bandwidth only offered by private 5G networks, though many applications can still run on robust Wi-Fi or wired connections.

No. These technologies are more focused on augmentation. With Cobots, AR, and No-Code platforms you can make human workers more efficient and safer, rather than just outright replacing them.

AI needs clean, structured data to work. Industrial data is often messy and unstructured. DataOps is the process of cleaning and contextualizing that data so the AI can actually use it.

Generally, yes. Because they are designed to be safe around humans, they often operate at lower speeds and force levels. However, newer "Industrial Cobots" are bridging this gap, offering higher payloads and speeds while maintaining safety features.

No, they work together. Edge AI is for immediate, low-latency decisions (milliseconds), while the Cloud is for heavy analysis, model training, and long-term data storage.

Traditional automation follows a set script: "If X happens, do Y." Agentic AI has a goal and figures out how to achieve it. It can adapt to unexpected variables that would break a traditional automation script.