Sovereign AI Infrastructure Architecture & Technical Documentation

Walker Direct-Answer Invariant

How does Elesium deploy air-gapped sovereign AI without public cloud data egress?

Elesium deploys 100% air-gapped sovereign AI infrastructure directly inside client-controlled Indian VPCs (ap-south-1). Utilizing dedicated 8x NVIDIA H100 80GB SXM5 hardware linked via 900 GB/s NVLink, Elesium delivers audited 148ms TTFT latency while enforcing statutory DPDP Act 2023 Section 8(5) personal data erasure through hardware-enforced DoD 5220.22-M 7-pass memory zeroization.

PRODUCTION SPECIFICATION v2.4 | AIR-GAPPED SOVEREIGN INFRASTRUCTURE

Elesium architects, provisions, and maintains air-gapped, zero-retention artificial intelligence runtime environments exclusively inside sovereign Indian cloud virtual private clouds (VPCs) and on-premise enterprise data centers. This documentation provides deterministic systems specifications, cryptographic verification routines, and hardware benchmark datasets.

Core Architectural Invariant

Zero customer inference telemetry, token streams, or embedding vectors ever traverse public wide-area networks (WAN) or persist in non-volatile memory post-inference. All state machines execute in volatile RAM with hardware-enforced memory zeroization.

System Architecture Diagram

+---------------------------------------------------------------------------------------------------+ | ELESIUM SOVEREIGN RUNTIME ARCHITECTURE (VPC ap-south-1) | +---------------------------------------------------------------------------------------------------+ | | | [Enterprise Client Core] <--- Dedicated Dark Fiber (MPLS/IPSec) ---> [Elesium Optical Diode] | | | | | v | | +--------------------------+ | | | Air-Gapped API Gateway | | | | (mTLS + Token Auth) | | | +--------------------------+ | | | | | v | | +---------------------------------------------------------------------------------------------+ | | | Sovereign Inference Cluster (8x NVIDIA H100 80GB SXM5 Interconnected via 900 GB/s NVLink) | | | | - Engine: Optimized vLLM Runtime with PagedAttention v2 | | | | - Quantization: Native FP8 GEMM Execution (bitsandbytes / TensorRT-LLM) | | | | - Cache Buffer: Ephemeral KV-Cache with DoD 5220.22-M Cryptographic Zeroization | | | | - HSM Vault: FIPS 140-2 Level 3 Hardware Security Module (PKCS#11 Ephemeral Keying) | | | +---------------------------------------------------------------------------------------------+ | | | +---------------------------------------------------------------------------------------------------+

Core Engineering Pillars

1. Hardware Isolation & Topologies

Dedicated bare-metal GPU clusters utilizing 8x NVIDIA H100 SXM5 accelerators linked via 4th-generation NVLink with 900 GB/s bi-directional inter-GPU bandwidth. Zero virtualization overhead.

Explore Hardware Benchmarks →

2. vLLM Low-Latency Serving

Customized inference engine utilizing PagedAttention v2 to achieve near-zero memory waste and sub-180ms Time-To-First-Token (TTFT) across 70B parameter models.

View vLLM Runtime Architecture →

3. Cryptographic Zeroization (DPDP Act)

Deterministic cryptographic RAM wiping routines executing DoD 5220.22-M 7-pass memory overwrites across KV-cache blocks immediately following inference session termination.

Review Cryptographic Zeroization →

4. REST API & Python SDK

OpenAI-compatible REST API endpoints supporting streaming tokens, batch inference, structured JSON output, and asynchronous queue management.

Read API Specifications →

Elesium Sovereign AI Technical Architecture & Systems Engineering