Edge intelligence,
designed from the transistor up.
Sudarshana Semiconductors pairs the hallucination-free Sudarshana machine-learning framework with the Vishwakarma family of processors — hardware and software conceived and engineered by the same team.
Sudarshana ML — compiled for the Vishwakarma. Hallucination-free by design.
One compiler, one runtime, one instruction set. The Sudarshana framework lowers models straight onto Vishwakarma silicon — no glue, no abstraction tax, no third-party stack. Every inference is verified against a formal bound before it is returned; what cannot be proven is refused.
- Graph compilervw-graph
- Sparse runtimevw-sparse
- On-device quantizervw-quant
- Fleet telemetryvw-signal
A 3nm phone SoC fusing a 4-topology NPU with always-on vision. Runs Sudarshana on-device, no cloud round-trip.
A sub-1W microchip for rings and watches. Streams sensor inference with continuous on-body learning.
A rack-scale edge node for factories, retail and towers. Deterministic latency under heavy real-time load.
A full training-and-serving accelerator for sovereign data centres. 256GB HBM, in-fab interconnect.
One team, the whole stack.
Co-design your next AI device.
From a single board to a sovereign data centre, our team engineers the silicon and the software together. Tell us what you are trying to run at the edge.