| Bottleneck | Why it matters |
|---|---|
| Token volume | Counts activity, including noise. It does not measure productive operator yield. |
| Subjective audits | Interpret past transcripts; they do not create an inspectable live measurement standard. |
| Model benchmarks | Measure the tool, not the human directing it. |
| Invisible skill | Teams, employers, and markets cannot distinguish high-yield operation from performative usage. |
| Yield formula | Cache read × output ÷ input²: defined inputs, defined output. |
| Privacy model | Exports four token counts, not private prompt content. |
| Five-metric signature | Rank, tier, and calibration across real operating behavior. |
| Gaming resistance | Benford-informed anomaly detection and SigArena stress testing. |
| Product | Market Opportunity | User Surface | Initial Focus |
|---|---|---|---|
| SIGRANK | $3–7B → $15–25B+ | AI Users | Builders, creators, students, researchers |
| AQUA | $9B → $20B+ | Applicants | Jobs, grants, funding, education |
| MO§ES™ | $0.3–0.9B → $5.8–15.8B | Institutions | Enterprise, government, platform deployments |
| SIGNOMY | $7.7B → $48–53B | Humans + Agents | Operators, agent creators, autonomous participants |
| Metric | Value |
|---|---|
| Total tokens | 3.719B |
| Cache read | 3.513B |
| Cache create | 132.25M |
| Operator input | 3.31M |
| System output | 70.25M |
| Amplification | 21.23× |
| Category | Players · Gap |
|---|---|
| Code agents | Cursor, Claude Code — no conservation guarantee. |
| Eval / guard | Braintrust, Patronus — no enforcement at execution. |
| Model providers | Anthropic, OpenAI, Google — no commitment across the stack. |
| MO§ES™ | A protocol — runs alongside, a layer beneath everything. |
| Asset | Status |
|---|---|
| MO§ES™ | Patent pending · 19/426,028. |
| AQUA Answer Bank™ | Proprietary application memory. |
| SigRank Metrics | Proprietary operator scoring. |
| SIGNOMY | Proprietary governance layer. |