- The short version — where India can actually win
- Stack map: design, IP, packaging, and foundry
- Unit economics: what moves margins for AI silicon
- Policy, grants, and talent flywheels
- Risks, bottlenecks, and an operator checklist
The short
- Design & packaging first. Indigenous foundry is a long game; near-term value sits in fabless IP and advanced packaging/test.
- Memory bandwidth is destiny. AI workloads are memory-bound; HBM access and interposer tech shape performance per watt.
- Don’t chase widest nodes for AI. Accelerators crave advanced nodes; for edge AI, mature nodes + NPU blocks can win.
- Talent clusters compound. Bangalore/Hyderabad design centres create a recruiting flywheel for domestic ventures.
Stack map: where value accrues
1) Fabless design & IP
RISC‑V cores, NPUs, and domain‑specific accelerators for inference at the edge (retail, industrial, autos). Moat IP + toolchains
2) Firmware, compilers, SDKs
Kernel optimisations and quantisation toolchains that squeeze perf from commodity silicon. Moat Developer lock‑in
3) OSAT: packaging, test, reliability
Advanced packaging (chiplets, 2.5D) and burn‑in testing. Revenue Higher ASPs per packaged part
4) Foundry & specialty processes
Domestic foundry is capex‑heavy and time‑intensive; specialty sensors and mature nodes can be a bridge.
Unit economics: sanity stack
| Driver | Why it matters | Notes |
|---|---|---|
| Node & yield | Perf/watt & die cost | Yields dominate gross margin for accelerators |
| HBM & packaging | Memory bandwidth | Interposers, chiplets, thermal budget are cost drivers |
| Software stack | Adoption friction | SDK maturity shortens POCs, drives stickiness |
| Volume commitments | Tooling amortisation | Pre‑buys reduce per‑unit costs and lead times |
Rule‑of‑thumb: If you can’t beat cutting‑edge nodes, win on system cost and developer experience.
Policy & talent
- Targeted grants for EDA, compilers, and ML runtimes, not just capex.
- Anchor orders via public deployments (edge AI in infra, health, agriculture).
- University shuttle programs to tape‑out on mature nodes for startups.
Risks & operator checklist
- Export controls on advanced GPUs; design for graceful degradation on commodity nodes.
- HBM supply concentration; secure multi‑year packaging partners.
- Talent churn; build ESOPs and academia partnerships.
- Pick a specific workload (e.g., vision at the edge) and optimise ruthlessly.
- Ship SDKs/docs early; treat developers as a first‑class customer.
- Model BOM under ±20% yield and memory price swings.