Deliverables
Typical outputs for this service.
- dataflow design
- quantization assumptions
- latency estimate
- target board constraints
- prototype RTL/HLS plan
Service
Edge AI / DSP pipeline prototyping
Prototype FPGA dataflow for quantized inference paths, streaming DSP pipelines and latency-oriented preprocessing blocks.
Scope
Deliverables
Scope is defined as reviewable engineering output.
Inputs required
Useful information for an initial review.
- Model, operator set or DSP chain
- Precision and quantization assumptions
- Input/output bandwidth
- Target board or device family
Limitations
Boundaries that prevent unsupported claims.
- No public production edge-AI benchmark suite is published yet.
- Power and throughput depend on board power delivery, memory topology and the exact operator mix.
Process
Engagement flow
The same review flow applies to public IP support, private prototypes and custom RTL work.
- Intake: workload, target, constraints and NDA requirement.
- Feasibility: architecture options, risks and evidence gaps.
- Implementation: RTL, wrappers, tests and docs where scope is approved.
- Review: simulation, build or measurement evidence before public claims.
Trust
Evidence and licensing references
Current public proof is intentionally limited to what can be inspected.
Catalog evidence model
Public examples should be evaluated through catalog status, verification level, limitations and linked evidence.
Licensing boundary
Commercial and proprietary use is handled by direct agreement where applicable.
Next step
Request Edge AI / DSP
Send the workload, target board or FPGA family, timing target, throughput goal, power constraints, interface assumptions and NDA requirement.