AI Evaluation Platform

SigRank is an AI evaluation platform for operators. Public, content-free, continuous, and governed — the only platform that evaluates the human, not the model or the output.

The only AI evaluation platform for operators.

Other platforms evaluate models or outputs. SigRank evaluates operators — the humans wielding AI — with public, governed, continuous evals.

Public

Results are visible on a public leaderboard, not locked in a private dashboard. Anyone can see the rankings, the Yield scores, and the operator class tiers. What gets measured publicly gets better publicly.

Content-free

Token counts only — never prompt content, never code, never conversation. The four token pillars (input, output, cache-read, cache-write) are sufficient to compute Yield without exposing what the operator is building.

Continuous

Evaluation runs from real session telemetry, not one-time test suites. The operator's skill is measured as it evolves, in production, over time. The leaderboard updates continuously.

Governed

The MO§ES framework defines the measurement specification, privacy boundaries, and public accountability requirements. This makes SigRank suitable for compliance contexts where auditable evaluation is required.

Platform architecture

SigRank is a read-only satellite leaderboard site that reads from signalaf.com's public API. The architecture is: MO§ES (governance framework) → Upsilon (measurement engine) → SigRank (public leaderboard) | SignalAF (public distribution). This site is the discovery surface; signalaf.com is the canonical source.

The platform is platform-agnostic — it works with Claude, GPT, Gemini, Cursor, Copilot, Windsurf, Codex, and any AI tool that produces token telemetry. Yield measures the human's cascade architecture, not the model's capability.

Υ = (cache_read × output) / input²

Public Operator Evals

The public evaluation layer for AI operators — ranked by Yield (Υ).

Developers

API documentation and developer resources for integrating with SigRank.

MCP Server

Model Context Protocol server for AI-assisted integration with SigRank.

How It Works

The full methodology behind Yield, token telemetry, and operator measurement.

FAQ

What is an AI evaluation platform?: An AI evaluation platform is a system that systematically assesses AI performance at scale. It defines what to measure, how to measure it, and how to present results. Existing platforms evaluate models (Vals AI, LMSYS Arena) or outputs (Braintrust, Langfuse). SigRank is the only AI evaluation platform for the operator layer — measuring the humans using AI.
How is SigRank different from other AI evaluation platforms?: SigRank is the only platform that evaluates operators, not models or outputs. It is public (results on a public leaderboard), content-free (token counts only, never prompt content), continuous (real session telemetry, not one-time tests), and governed (by the MO§ES framework). Other platforms are either private (Braintrust, Langfuse) or model-focused (Vals AI, LMSYS Arena).
How does SigRank protect privacy?: SigRank is privacy-preserving by design. It collects token counts only — the four pillars of input, output, cache-read, and cache-write. It never collects prompt content, response text, source code, or conversation. Yield (Υ) = (cache_read × output) / input² is computed entirely from numeric telemetry. The evaluation is public; the work is private.
How do I integrate with the SigRank platform?: SigRank reads from signalaf.com's public API. Developers can access leaderboard data, operator profiles, and metrics programmatically. An MCP server is also available for AI-assisted integration. Visit signalaf.com/score to enroll as an operator and submit token telemetry. See the developers page for API documentation and the MCP page for the model context protocol server.

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Platform architecture

Υ = (cache_read × output) / input²

FAQ

What is an AI evaluation platform?

An AI evaluation platform is a system that systematically assesses AI performance at scale. It defines what to measure, how to measure it, and how to present results. Existing platforms evaluate models (Vals AI, LMSYS Arena) or outputs (Braintrust, Langfuse). SigRank is the only AI evaluation platform for the operator layer — measuring the humans using AI.

How is SigRank different from other AI evaluation platforms?

SigRank is the only platform that evaluates operators, not models or outputs. It is public (results on a public leaderboard), content-free (token counts only, never prompt content), continuous (real session telemetry, not one-time tests), and governed (by the MO§ES framework). Other platforms are either private (Braintrust, Langfuse) or model-focused (Vals AI, LMSYS Arena).

How does SigRank protect privacy?

SigRank is privacy-preserving by design. It collects token counts only — the four pillars of input, output, cache-read, and cache-write. It never collects prompt content, response text, source code, or conversation. Yield (Υ) = (cache_read × output) / input² is computed entirely from numeric telemetry. The evaluation is public; the work is private.

How do I integrate with the SigRank platform?

SigRank reads from signalaf.com's public API. Developers can access leaderboard data, operator profiles, and metrics programmatically. An MCP server is also available for AI-assisted integration. Visit signalaf.com/score to enroll as an operator and submit token telemetry. See the developers page for API documentation and the MCP page for the model context protocol server.