SOLUTION 03 OF 04
Custom AI Accelerator
Purpose-built acceleration for the workload you actually run — not a general-purpose approximation of it.
WHO IT'S FOR
Is this the right starting point?
Battery- or thermally-limited devices
Where every watt shortens runtime or adds a heatsink.
Products shipping at volume
Where per-unit silicon cost and efficiency decide margins.
Teams needing a trusted source
Where a domestically designed accelerator, with IP held in India, matters.
ENGAGEMENT OPTIONS
Three ways to get an accelerator
FASTEST PATH
Start from Clean Future CF-1
Adapt our low-power edge AI accelerator to your workload and product.
About CF-1 →
FOR SOC TEAMS
Accelerator IP
Integrate a workload-matched accelerator block into your own system-on-chip.
Discuss IP →
FULL CUSTOM
Designed from scratch
An accelerator architected around your workload from the first profile.
Discuss a design →
WHAT YOU GET
Deliverables
Workload-matched architecture
Sized to your models' compute, memory, and latency needs — nothing idle.
Design deliverables
RTL and IP deliverables, scoped to your integration needs.
Software support
Model compilation and runtime support for your frameworks [confirm scope].
FPGA-validated prototype
Proven on real hardware against your workload before tapeout.
Path to silicon
Tapeout support, with packaging and test as our Uttar Pradesh line comes online.
HOW IT WORKS
The engagement, step by step
Timeline depends on the engagement option and scope: [__] months typical.
STEP 1
Profile
Workload Intelligence sets the performance-per-watt target.
STEP 2
Explore
Candidates simulated and compared on evidence.
STEP 3
Design
RTL design and verification of the chosen architecture.
STEP 4
Validate
FPGA prototype tested on your real workloads.
PLATFORM STAGES USED
Where this sits in the loop
Build acceleration around your workload
Tell us what your device needs to run and the power it has to run on.
Talk to us
— From AI to Silicon
© [Year] PathinAI Technologies Private Limited