SCOI Atlas · L0 Infrastructure
L0D Compute & State Infrastructure
Vector DBs, object stores, feature stores, KV caches — persistent state around ephemeral compute.
TL;DR · Direct answer
L0D Compute & State Infrastructure is a sublayer of L0 Infrastructure in the Supply Chain of Intelligence™ (SCOI) by Anand Arivukkarasu. It is a required capability but not on its own a durable moat. Storage architecture is the difference between an agent that learns and one that only remembers the last message.
What actually matters at L0D
- KV-cache reuse is now a first-class cost lever, not an optimization.
- Vector DB choice matters less than embedding + reranker choice.
- Feature stores return in the agent era as memory stores.
The startup lens
Storage architecture is the difference between an agent that learns and one that only remembers the last message.
Vertical lens — how this plays across categories
Vertical AI SaaS
Own a proprietary embedding of your customer data — the moat is the vector, not the DB.
AI infra
Cache-aware routing between models is a real product.
Consumer AI
Per-user memory index is a retention feature.
How to defend L0D
- Custom embeddings on proprietary data (L1B linkage).
- Contracts and portability for the vector index.
Other sublayers in L0 Infrastructure
L0A
Silicon & Memory
Accelerators (Nvidia, AMD, TPU, Trainium, custom), HBM, and the memory hierarchy that dominates training cost.
L0B
Data Centers
Powered shells, colo, hyperscale — the physical containers of intelligence.
L0C
Interconnect Fabric
NVLink, InfiniBand, Ethernet-based scale-out — the pipes between accelerators.
L0E
Edge & On-Device Compute
NPUs in phones, laptops, cars, wearables and industrial devices.