Adaptive Early-warning Governor for Internal Stability

Detect instability early. Contain the damage.

AEGIS monitors training health in real time and detects qualifying instability as it emerges—not only after a run has already degraded. It plugs into the training loop as an operator-controlled governance layer. Choose the intervention policy that is right for your stack: alert, checkpoint, quarantine, halt, or adaptive braking.

Qwen3-1.7B · 5 fresh seeds5 / 5

governed pairs benefited at the primary disturbance-containment milestones

Llama-3.2-1B · 5 fresh seeds5 / 5

governed pairs benefited at every reported recovery milestone

Qwen3-4B · 3 fresh seeds26.4%

aggregate reduction in downstream damage area, with benefit in 3 / 3 pairs

What the system does

Observe. Choose. Respond.

AEGIS plugs into the live training loop without taking ownership away from the training team. It monitors continuously, separates detection from authorization, and routes a qualifying event into the response contract the operator selected.

01 · Observe

Monitor training health

AEGIS watches proprietary model-internal signals alongside ordinary loss and evaluation telemetry while the run is still active.

02 · Choose

Set the response contract

Choose alert-only monitoring, checkpointing, quarantine, halt, adaptive braking, or a staged combination that fits your operating environment.

03 · Respond

Act within limits

When the agreed authorization gate is met, AEGIS executes or recommends the selected policy while disengagement rules and operator override remain intact.

Evidence boundary.

Prospective studies currently validate the integrated detection-and-adaptive-braking loop for a registered disturbance class across Qwen and Llama from approximately 1B through 4B parameters. Adaptive braking is the validated end-to-end demonstration, not a prescribed deployment policy. Other response policies and disturbance classes require customer-specific validation.

External validation

Choose the response contract before it is needed.

The design-partner path begins in shadow mode: measure signal behavior, alert quality, monitoring cost, and qualifying-incident exposure. Then select the response contract—alert, checkpoint, quarantine, halt, adaptive braking, or a staged combination—that fits the training stack.