Responsibility · Responsible Scaling Policy

How we scale models. Without scaling the harm.

Scaling model capability has to be paired with scaling our ability to red-team, disprove, and govern. We scale only when the safety posture scales with the capability. This page is the public framework.

Four safety levels. Each with required controls.

SL-1 — Bounded inline

Lino-class (1B)

On-device only. No exfiltration paths. Sub-100ms p95. Signed weights verified at install. Deployable on any developer machine; no network egress required.

On-device inference
Signed sigstore weight bundles
Local-only telemetry by default
Air-gap-compatible

SL-2 — Multi-tenant cloud

Eagle 13B · Griffin Lite 8B · Griffin S 14B

Multi-tenant inference; structured trace contract; per-tenant audit log; standard adversarial-resistance gate (≥0.94 prompt-injection block-rate).

Per-tenant Postgres + Redis isolation
Structured trace contract enforced at decoder
Adversarial-resistance regression gate
Customer-controlled audit log streaming

SL-3 — Dedicated reasoning

Griffin M 32B · Griffin L 70B

Single-tenant inference cluster; advanced adversarial-resistance gate (≥0.97); coordinated-disclosure obligations; quarterly red-team rotation; structured-trace human audit on 300 samples per release.

Single-tenant GPU pool
Advanced adversarial gate
Coordinated disclosure SLA committed in contract
Quarterly external red-team rotation

SL-4 — Sovereign deep reasoning

Griffin Zero (671B-MoE)

Air-gapped or VPC-isolated. Full red-team + manual trace audit per release. Customer-controlled key material. ITAR/export-control review. Adversarial-resistance ≥0.99.

Air-gapped or VPC-isolated deployment
Customer-controlled key material
ITAR / export-control review per release
Manual trace audit on every release

What triggers a re-tier.

If safety regresses, the tier ceiling lowers. The model continues to ship — but at the lower safety level — until the posture catches up. The triggers:

  • Adversarial-resistance regression > 0.5% on the held-out suite
  • Hallucination-rate regression > 0.1% on the security-Q&A eval
  • Refusal-rate regression > 5% on legitimate-research prompts
  • Novel jailbreak class observed in MCP-server traffic or red-team logs
  • Customer-facing safety incident attributed to model behaviour
  • External regulatory or sectoral requirement change affecting deployment posture

How we govern this.

Internal safety review board

Weekly review of red-team findings, eval regressions, and customer safety reports. Membership rotates across engineering, research, and security.

External red-team partners

Quarterly rotation of independent red teams with sector-specific specialisations (offensive security, prompt injection, AI safety).

Public RSP commitments

This page is the public commitment. Updated quarterly. Material changes flagged on the changelog.

Independent audit

Annual third-party audit of the eval methodology, the corpus curation, and the release pipeline. Summary published in the transparency report.

Talk to us about the safety posture.