CI-1T | Stability Engine

CI-1T

Real-time stability engine for critical systems.
Detects the failures that look like success.

<200ms

API response

Zero config

no training period

Fully tunable

thresholds & weights

Your model passed every test.
It's still wrong in production.

Traditional monitoring catches crashes and errors. But the most dangerous failures don't look like failures at all. Your system returns confident outputs, metrics stay green, and no alarm fires. We call these ghosts.

Looks stable

Low variance, consistent outputs. Traditional metrics say everything is fine.

Sounds confident

High softmax probabilities. The model is sure of itself, just sure of the wrong thing.

Silently wrong

The prediction is incorrect, but nothing flags it. This is a ghost, and it's already in production.

One API call. That's it.

Send your scores. CI-1T tells you if something is wrong, even when everything looks right.

Send scores

POST your scores to /evaluate. Model probabilities, sensor readings, financial signals. Any numeric data.

Get CI score

The engine computes a Collapse Index in nanoseconds. Low = stable. High = drifting. The response includes authority level, warnings, and fault status.

Catch ghosts

CI-1T watches for suspiciously stable patterns across episodes. If a ghost is confirmed, you know before your users do.

See it in action

A single curl call. Real response. No SDK required.

POST /evaluate

$ curl -X POST https://ci-1t-api.onrender.com/evaluate \
  -H "Content-Type: application/json" \
  -d '{"scores": [32768, 32768, 32768]}'

Response

{
  "ci_out":          145,        // low = stable
  "ci_ema_out":      145,        // smoothed trend
  "al_out":          0,          // authority: trusted
  "warn":            false,
  "fault":           false,
  "ghost_suspect":   false,
  "ghost_confirmed": false      // no ghost here
}

What other tools miss

Traditional monitoring tracks when things break. CI-1T tracks when things stop changing. That's the real danger signal.

Traditional monitoring

CI-1T

Alerts on errors & crashes

Alerts on silent stability

Needs weeks of baseline data

Works on the first call

Requires model access or logs

Only needs raw output scores

Confident + wrong = invisible

Confident + wrong = ghost detected

Where it works

One engine. Many domains.

ML Model Monitoring

Detect ghosts: models that are stable, confident, and silently wrong. Track suspect patterns across episodes and catch failures that pass every test.

Marketplace & Trust

Monitor vendor behavior across thousands of sellers. Detect pricing manipulation, fake review patterns, and trust score collapse before they damage your platform.

Sensor & IoT Systems

Catch stuck sensors, flatline readings, and signal drift. When CI equals zero, your readings are identical. That's either perfect calibration or a dead sensor.

Financial Models

Monitor credit scoring, fraud detection, and pricing models for output collapse. Detect when a model locks onto one answer and stops responding to new data.

Fleet & Multi-Node

Compare outputs across replicas in a single call. Cross-node detection catches the instance that agrees with itself but disagrees with the fleet.

Content Moderation

A moderation model that confidently labels harmful content as "safe" is a textbook ghost. Track classifier drift across categories and catch silent failures before they reach users.

Your model passed every test.It's still wrong in production.

One API call. That's it.

See it in action

What other tools miss

Where it works

Pay as you go. No subscriptions.

Your model passed every test.
It's still wrong in production.