NumericalAI brings Palace — a research-grade, GPU-accelerated 3D finite-element electromagnetics solver — to superconducting quantum hardware teams. The platform is browser-based, runs on enterprise-class GPUs, and is accessible without local HFSS/CST licenses, meshing tools, or HPC procurement. It targets the exact electromagnetic questions that decide whether a quantum processor works: qubit and resonator mode frequencies, quality factors, cross-coupling, and dielectric loss participation. Palace eigenmode analysis recovers transmon and resonator frequencies and Q-factors directly from the chip layout, electrostatic extraction returns the full capacitance matrix between islands and ground, and driven frequency-domain solves characterise readout and Purcell-filter response. The bundled AI Copilot — an LLM trained on the solver documentation — translates plain-English design questions ("what is the participation ratio of the substrate-metal interface in this qubit?") into ready-to-run case files, so quantum engineers iterate in a chat session instead of waiting on a specialist. For quantum hardware groups, the payoff is direct: each fabrication-and-cryostat characterisation cycle costs tens of thousands of dollars and weeks of fridge time, and simulation-first design lets teams converge frequencies, anharmonicities, and loss budgets in software before committing a single tape-out — compressing roadmap milestones that otherwise gate the entire program.

NumericalAI brings Palace — a GPU-accelerated 3D finite-element electromagnetics solver — to chip, package, and board engineers. The platform is browser-based and accessible without local commercial EM licenses, meshing seats, or HPC procurement, and it covers the field-solve workloads that gate modern electronics: capacitance and inductance extraction, transmission-line and via modelling, and broadband S-parameter characterisation of interconnect and packaging. Electrostatic and magnetostatic solves return the parasitic capacitance and inductance matrices that drive timing and power-integrity models, while driven frequency-domain analysis produces the S-parameters and impedance profiles that decide whether a high-speed link closes. The bundled AI Copilot turns plain-English questions ("what is the differential impedance of this stripline pair, and where does it discontinuity?") into ready-to-run Palace cases, removing the queue for the scarce in-house EM specialist. For semiconductor and electronics organisations, the result is measurable: high-fidelity field solves replace late, expensive discoveries on silicon and PCB respins ($100K+ each, plus weeks of schedule), commercial per-seat EM licenses are replaced by pay-per-GPU-hour compute, and design, packaging, and SI teams collaborate on a shared, auditable set of cases.

NumericalAI brings Palace — a GPU-accelerated 3D finite-element electromagnetics solver — to RF, microwave, and telecom hardware teams. The platform is browser-based and accessible without local commercial EM licenses or HPC procurement, and it targets the workloads that define wireless performance: antenna radiation, cavity and resonator filters, waveguide modes, and broadband S-parameter response. Driven frequency-domain analysis produces return loss, insertion loss, and full S-parameter matrices; antenna solves recover radiation patterns, gain, and impedance match; and eigenmode sweeps tune resonant filters and cavities to spec. The bundled AI Copilot translates plain-English design questions ("what is the gain and front-to-back ratio of this patch array at 28 GHz?") into ready-to-run Palace cases, so RF engineers iterate without queueing for the senior simulation expert. For telecom OEMs, RF module suppliers, and infrastructure vendors, the payoff is direct: simulation-driven design replaces large fractions of anechoic-chamber and network-analyzer bench time ($5K–$50K/day), filter and antenna tuning cycles compress from weeks to hours, and 5G/6G link-budget risk is bounded in software before hardware is fielded.

NumericalAI brings Palace — a GPU-accelerated 3D finite-element electromagnetics solver — to aerospace and defense electromagnetics teams. The platform is browser-based and accessible without local commercial EM licenses or HPC procurement, and it covers the high-consequence workloads these programs depend on: radar and conformal antenna radiation, radome transmission, waveguide and feed networks, magnetics, and platform-level EMC/EMI. Antenna and radiation solves recover patterns, gain, and sidelobe behaviour for apertures and conformal arrays; eigenmode analysis characterises waveguide and cavity feeds; and magnetostatic solves support sensors and actuators. The bundled AI Copilot turns plain-English questions ("how does this radome dielectric stack-up distort the boresight pattern?") into ready-to-run Palace cases, so analysts spend time on requirements, not solver setup. For aerospace OEMs, defense primes, and their suppliers, the result is direct: high-fidelity field solves replace scarce antenna-range and EMC-chamber time and reduce prototype iterations, design margins on radar, antenna, and EMC requirements are established earlier, and cross-functional teams collaborate on a shared, auditable case base — all on GPU infrastructure procured by the hour rather than as capex.

NumericalAI brings Palace — a GPU-accelerated 3D finite-element electromagnetics solver — to automotive electronics and connectivity teams. The platform is browser-based and accessible without local commercial EM licenses or HPC procurement, and it targets the electromagnetics that increasingly decide vehicle programs: ADAS radar, V2X and connectivity antennas, wiring-harness signal integrity, and platform EMC/EMI. Antenna and driven frequency-domain solves characterise 77 GHz radar apertures and connectivity antennas in their installed environment, while transmission-line and signal-integrity analysis bounds harness crosstalk and high-speed link behaviour. The bundled AI Copilot converts plain-English questions ("how does bumper fascia curvature shift my radar antenna pattern?") into ready-to-run Palace cases, removing the dependency on a scarce EM specialist for early studies. For automotive OEMs and tier-1 suppliers, the result is direct: simulation-first design reduces full-vehicle EMC-lab re-test cycles ($50K–$500K each plus weeks of schedule), antenna placement and harness routing are de-risked before hardware exists, and electronics, connectivity, and EMC teams iterate in software on a shared, auditable case base.

NumericalAI brings Palace — a GPU-accelerated 3D finite-element electromagnetics solver — to power-electronics and energy-systems engineers. The platform is browser-based and accessible without local commercial EM licenses or HPC procurement, and it covers the magnetics and field workloads that drive efficiency, thermals, and EMI in power hardware: inductance and loss extraction, busbar and interconnect modelling, and magnetic-component design. Magnetostatic solves recover the inductance and current-distribution behaviour of busbars, coils, and transformer windings, while electrostatic and driven analyses support insulation, capacitance, and EMI studies. The bundled AI Copilot turns plain-English questions ("what is the loop inductance of this power-module busbar layout?") into ready-to-run Palace cases, so power engineers iterate without queueing for an EM specialist. For energy OEMs, power-electronics suppliers, and grid-hardware teams, the payoff is direct: high-fidelity field solves reduce physical magnetics-prototype spins, EMI and loss problems are bounded before they reach qualification, and design teams work on GPU infrastructure procured by the hour rather than via per-seat EM licenses and HPC capex.

NumericalAI brings Palace — a GPU-accelerated 3D finite-element electromagnetics solver — to consumer-electronics engineering teams. The platform is browser-based and accessible without local commercial EM licenses or HPC procurement, and it targets the workloads that decide whether a device passes certification and performs in the hand: embedded antennas, radiation and exposure, signal integrity, and multi-radio coexistence. Antenna and driven frequency-domain solves recover radiation efficiency, return loss, and patterns for the cramped antennas inside phones, wearables, and IoT modules, while transmission-line analysis bounds signal integrity on dense boards. The bundled AI Copilot turns plain-English questions ("how does the user's hand detune this wearable antenna?") into ready-to-run Palace cases, removing the wait for a centralised EM specialist that is rare in fast-moving CE organisations. For consumer-electronics OEMs and ODMs, the result is direct and easily quantified: simulation-first design replaces board-spin-and-measure iteration, antenna, radiation, and coexistence risk is bounded before certification, and differentiated products reach the shelf months sooner — all on GPU compute billed by the hour rather than per-seat EM licenses.

NumericalAI brings Palace — a GPU-accelerated 3D finite-element electromagnetics solver — to industrial and manufacturing engineering teams. The platform is browser-based and accessible without local commercial EM licenses or HPC procurement, and it covers the electromagnetics behind factory and product hardware: capacitive and inductive sensors, induction heating, eddy-current non-destructive testing, and electric-machine components. Electrostatic and magnetostatic solves extract the capacitance and inductance behaviour of proximity and position sensors and of coils and windings, while driven analyses support induction-heating and eddy-current NDT studies. The bundled AI Copilot turns plain-English questions ("what is the sensitivity of this inductive proximity sensor to target distance?") into ready-to-run Palace cases, so engineers iterate without a dedicated EM specialist. For industrial OEMs, automation suppliers, and equipment builders, the result is direct: high-fidelity field solves replace bench-prototype iteration on sensors and magnetics, performance and EMI issues are bounded before tooling is committed, and teams run on GPU compute billed by the hour rather than per-seat EM licenses and on-prem HPC.