◆ Gentoo Logic · Modeling Warehouse

Architecture comparison

Anduril vs Shield AI

Shield AI runs closer to the foundational model (Native (own / self-hosted weights)) than Anduril (Off the LLM map (in-house non-LLM ML)). No shared foundational model — different bets.

Anduril

Defense

Proximity
Off the LLM map (in-house non-LLM ML)
Models
Cloud · datastore
HybridProprietary internal telemetry stores (Lattice platform)Data lake/warehouse for long-term sensor/log storage (likely cloud + on-prem, exact vendors undisclosed)Streaming/message bus layer (Kafka/Pulsar-like per system design guidance, not confirmed as production)
Compliance
ITAR (International Traffic in Arms Regulations) – required for US defense exports and autonomous weapons systemsDoD cybersecurity controls (e.g., NIST SP 800-53 / FedRAMP-aligned baselines for handling defense telemetry)SOC 2–style controls for hyperscale manufacturing and software-defined facilities (inferred from defense SaaS norms)Defense-specific secure manufacturing and export controls for Arsenal-1 and international facilities
Architecture

Anduril’s production architecture is built around its proprietary **Lattice** autonomy platform as the software backbone for autonomous systems and the **Arsenal** software-defined manufacturing stack, integrating sensor fusion, decision logic, and production control across a mix of cloud and tightly controlled on‑prem deployments.[10][12][13] Public material focuses on capabilities and manufacturing rather than concrete cloud/database vendor disclosures, so specific underlying services (e.g., exact clouds and DB engines) remain intentionally opaque.[3][10][12]

Shield AI

Defense

Proximity
Native (own / self-hosted weights)
Models
proprietary / self-built models
Cloud · datastore
Hybridown
Compliance
FedRAMP
Architecture

Builds Hivemind, its own autonomy foundation for GPS/comms-denied flight.

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