IN Brief:
- Taoglas has released an AI-driven antenna selection tool and will demo it at embedded world 2026.
- The engine is positioned to account for real integration factors, including PCB layout, enclosure effects, and multi-radio coexistence.
- The platform sits within Taoglas’ AntennaXpert toolchain, linking selection through to integration workflows.
Taoglas has introduced an AI-driven Antenna Product Recommendation Engine designed to accelerate early-stage antenna selection by translating design constraints into a validated shortlist, with the company planning live demonstrations at embedded world 2026 in Nuremberg from March 10–12.
The platform is aimed squarely at the problem RF teams have lived with for decades: antenna selection is often treated as a component choice, yet the real performance outcome is dominated by integration — ground clearance, housing materials, keep-out discipline, proximity to noisy subsystems, and the compromises forced by multi-radio coexistence. Taoglas says the new engine factors variables that datasheets do not capture well, including PCB layout effects, enclosure impacts, and multi-radio operation, enabling a faster move from initial requirement to shortlist.
In its product positioning, Taoglas links the tool to the downstream consequences of a weak starting choice: failed radiated performance, last-minute mechanical changes, retuning cycles, and schedule damage around compliance testing. The company is putting the engine under its broader AntennaXpert umbrella, alongside digital tools for configuration, cable selection, and guided PCB integration support.
“Choosing the right antenna has traditionally depended on individual experience, undocumented expertise, and extensive manual comparison,” said David Connolly, Global Product Management Director at Taoglas. “This recommendation engine is a game-changer. We’ve distilled our RF knowledge into an intuitive tool that delivers answers on demand, whether you know exactly what you need or you’re still defining your application.”
Taoglas says the engine is trained on real-world design knowledge built from its project history, using that dataset to scan, filter, and rank suitable antenna options in minutes. That approach implicitly acknowledges a stubborn reality in embedded wireless: parametric filters rarely model the true boundary conditions, while in-house RF expertise is unevenly distributed, and mistakes show up late when the antenna finally meets the enclosure and the rest of the board.
At embedded world, Taoglas plans to show the engine operating under practical constraints and to pair it with access to RF specialists for integration trade-offs. The company is also using the event to highlight its broader antenna portfolio across modern wireless categories, spanning Wi-Fi 6/7, UWB, NTN, DECT, ISM, and combinations integrating GNSS and cellular alongside Wi-Fi.
The more immediate implication is workflow change rather than a single product launch. As electronics teams push more connectivity into smaller platforms, with tighter mechanical packaging and increased radio density, selection and integration are converging into a single iterative loop. Tooling that forces that loop earlier, and documents the assumption set behind the antenna choice, tends to reduce rework even when it does not eliminate it.
