Silicon where latency still matters.
RTL-first FPGA engineering for video, embedded AI, and RF workloads that need determinism, not approximation.
Workloads
Video, AI, and RF
The emphasis is on pipelines that need predictable latency and clear resource trade-offs.
Platforms
AMD Xilinx focus
Artix and Zynq families, with the toolchain and board-level decisions treated as part of the work.
Outputs
Timing with context
Constraints, reports, and integration notes arrive with the implementation instead of after it.
Talk to FPGA engineering
Send a work email and a few details on workload, platform, or timing pressure. We’ll reply with a practical view on fit and next steps.
What this engagement should protect
FPGA work gets expensive when the architecture is vague or the handoff is incomplete. The goal here is to make the critical decisions early and document them cleanly.
Outcome
Architected around timing
The implementation starts from throughput, latency, and determinism rather than from generic acceleration language.
Outcome
Hardware and software partitioning
When Zynq or hybrid systems are involved, the split between programmable logic and software is kept explicit.
Outcome
Validated before handoff
Bench evidence, constraints, and build artifacts arrive together so the next team is not reverse-engineering the intent.
Selected scope
The work tends to centre on the parts of FPGA programs that are hardest to improvise later: platform choice, timing-sensitive architecture, HW/SW boundaries, and board-level realities.
Workload
Real-time video pipelines
Capture, processing, transport, and deterministic low-latency paths for systems where delay and throughput both matter.
- Latency-led pipeline structure
- Interface and bandwidth awareness
- Build choices documented for review
Workload
Embedded AI acceleration
Acceleration paths for inference workloads where CPUs and GPUs drift too far from the timing or power budget.
- Resource-aware partitioning
- Data movement kept explicit
- Integration with surrounding compute considered early
Workload
RF and sensing systems
FPGA work for RF, SDR, and sensor-rich systems where deterministic signal handling matters at the edge.
- Signal-path discipline
- Interface and clocking awareness
- System context retained in the implementation
Platform
Platform and board integration
FPGA selection, memory and I/O planning, and optional board work when the programmable logic needs a cleaner hardware home.
- Artix and Zynq fit analysis
- Power, I/O, and clock considerations
- Optional FPGA-centric PCB collaboration
Working style
A measured sequence built to reduce ambiguity around workload fit, timing priorities, and the eventual integration path.
- 01
Frame the workload
We start with the data path, latency budget, interfaces, and the real reason the work belongs in programmable logic.
- 02
Choose the architecture
Platform fit, HW/SW partitioning, and toolchain choices are settled while the design is still flexible.
- 03
Implement and verify
RTL, constraints, and build outputs are developed with timing and integration evidence kept visible.
- 04
Release with confidence
The handoff includes not just the design but the reports and context needed to continue safely.
Typical deliverables
The emphasis is on outputs that can survive review by hardware, software, and systems teams without additional translation.
Deliverable
RTL package
HDL sources, constraints, and the implementation material needed to reproduce the work.
Deliverable
Timing and performance record
Reports and supporting notes that explain what the implementation is doing and where the margins sit.
Deliverable
System architecture brief
Block-level context for interfaces, partitioning, and the boundaries around the programmable logic.
Deliverable
Optional hardware support
Board-level collaboration when the FPGA choice and the physical platform need to be resolved together.
Related disciplines
Adjacent services for teams working across the stack.
Map the workload before the board.
If the latency budget is unforgiving or the acceleration strategy is still vague, we can help turn that into a cleaner FPGA direction and a more reviewable implementation path.