Important claims are tied to a reproducible configuration, measurement and owner.
WHY MAGIC LENS
Senior systems judgment, still close to the implementation.
More than fifteen years of capability across FPGA, DSP, software-defined radio, embedded systems, emulation, verification and technical leadership, focused on the product boundary where disciplines must converge.
CAPABILITY LINEAGE
From signal intent to working system.
Deep DSPModem, baseband, radar, LiDAR, imaging and navigation
Full stackModel, RTL/HLS, firmware, host and lab
Pre-siliconEmulation, prototyping, firmware and workloads
ProductsSpace, medical, autonomy, SDR and storage
The recurring problem is not “write an RTL block.” It is to make a difficult product boundary coherent, observable and provable across disciplines.
Representative capabilities include microsatellite payload data paths; automotive LiDAR and perception acceleration; medical imaging; rugged navigation and SDR; base-station algorithm migration and cloud FPGA execution; PCIe/DMA and storage-controller systems; multi-FPGA prototyping; firmware-ready emulation; and target-hardware validation.
Work can span golden algorithms, fixed-point tradeoffs, FPGA architecture and RTL/HLS, embedded processors and drivers, host software, system interfaces, emulation/prototyping infrastructure, CI/regression operations and end-to-end evidence.
The operating principle is simple: keep product intent, implementation decisions and acceptance evidence connected. AI agents increase the rate of exploration and artifact production; deterministic engineering tools and accountable review decide what is trustworthy.
OPERATING PRINCIPLES
How the work is governed.
Algorithm, FPGA, firmware, host, board and test are planned against one product boundary.
AI-created implementation and tests remain untrusted until reviewed and verified.
Data, model and deployment choices reflect written IP, confidentiality and security constraints.
A separate review pass challenges assumptions, trace gaps and unsupported conclusions.
Documentation, runbooks, training and reproducible flows make the capability durable.