Apple Silicon / on-device
Local model iteration for teams and individual developers.
Device/runtime setup notes.
Security
Random Walk defines data boundaries, access permissions, evaluation evidence, runtime logs, and ownership from the start of each private AI project.

Boundary
Training material, dataset packages, model weights, LoRA adapters, fused models, inference environments, external interfaces, and storage locations all belong in the boundary design.

Local model iteration for teams and individual developers.
Device/runtime setup notes.
Training and inference inside company-owned compute.
Environment record and operator runbook.
Dedicated private infrastructure with controlled access paths.
Architecture diagram and access notes.
Deployment inside the customer's own approved cloud boundary.
Data movement register and runtime record.
Systems designed for restricted or disconnected environments.
Transfer procedure, update path, and evidence handling notes.
Inference near devices, operators, sensors, or industrial workflows.
Fleet update model and lightweight runtime notes.
Evidence
Data sources, processing steps, training configuration, model fusion, evaluation, deployment versions, call records, and key changes should be traceable.

Responsibility
We define who provides data, who approves use, who maintains environments, who reviews evaluation, and who makes release decisions. Systems with unclear ownership do not last.

Architecture, access-path design, deployment runbooks, evaluation evidence, documentation packages, and customer-side review support.
Legal basis, policy approval, identity provider policy, user provisioning, internal audit, certification, and regulatory filings.
Compliance-aware engineering support. Formal legal, regulatory, and certification determinations remain with the customer and qualified advisors.