Technology Proof KPI Disclosure

Only the minimum indicators needed to verify NoahAI operating scale and reliability are public.

Purpose of disclosure

This is not an internal management dashboard. It provides four aggregate indicators so business, investment, and technology reviewers can verify NoahAI operating scale, event-collection reliability, and AI inference and learning pipelines.

As of Aug 5, 2026 · recent 30 days

Technology Operations Proof Snapshot

We publish only the operating scale, system reliability, and AI processing evidence needed for business and investment review. Internal user, transaction, venue, and revenue analytics are excluded.

Technology operation events

Judgment, learning, guardrail, recovery, and related telemetry

Event processing reliability

Successfully collected / total technology events

AI inference operations

ai_inference_completed

Learning-data records

learning_data_recorded

Validation scope

AI judgment and inference · learning-data records · guardrail and recovery events · multi-asset adapter validation

These are technology-operation indicators, not user scale, revenue, trading performance, or a promise of future returns.

As of: ·Collection baseline: v

Disclosure scope and formulas

The four public indicators

Technology operation events

A recent 30-day aggregate across judgment, learning, guardrail, recovery, and related operating pipelines.

Event processing reliability

The share of technology events collected successfully. It is not order success or trading return.

AI inference operations

The scale of completed inference processing in the AI judgment pipeline.

Learning-data records

The scale of standardized learning data recorded for validation and improvement.

Internal information not disclosed

The following data is not required for technology proof and could reveal user, commercial, affiliate, or operating strategy, so it remains internal.

  • User scale, activity, and return analysis
  • Order attempts, transaction frequency, and per-user activity
  • Volume, position lifecycle, and account performance
  • Venue share and concurrent venue usage
  • Revenue, costs, affiliate economics, and strategy parameters

Disclosure principles

  • Publish only the minimum aggregate evidence needed to explain the technology.
  • Show the as-of date, aggregation window, and working-source version.
  • Never interpret technology-event reliability as trading performance or return.
  • Keep user, transaction, affiliate, and revenue details inside internal BI.
View sanitized public JSON