Early access · in development

Prove your AI investment is actually working.

Stop tracking activity. Start tracking outcomes. Tokenomia translates raw token usage into business-ready attribution.

info A cautionary tale, not a hypothetical

“Uber burned its entire 2026 AI coding budget in about four months after an internal usage leaderboard rewarded raw token consumption with no way to prove it produced shipped value. That link is not there yet.”

Paraphrased from Uber COO Andrew Macdonald · Fortune, TechCrunch (2026)

Attribution Flow v1.0

hubVerified Outcomes

Tokens Consumed

Shipped Value ($k)

trending_up+3.4x ROI

Token Velocity4.8M /wk

Defect Escape-31.4%

Attribution Ratio94.2%

Continuous LLM Sync Zero Synthetic Overhead

Illustrative example — figures shown are for demonstration only, not real customer results.

Market Reality

Goodhart’s Law in the AI Era

When a measure becomes a target, it ceases to be a good measure. We analyzed the fallout from “proxy-only” AI tracking.

Amazon

trending_down

An internal leaderboard nicknamed “Kirorank” led employees to direct AI agents to do unnecessary work just to climb rankings — the industry now calls this “tokenmaxxing.” Amazon shut it down and switched its target metric away from raw token counts.

HCAMag · Gartner · 2026

METR

speed

A randomized controlled trial found experienced developers using AI tools were measurably 19% slower on real tasks — yet they still believed afterward they’d been sped up by 20%.

METR, independent RCT

Deloitte

query_stats

An independent survey of 1,854 executives found just 6% of organizations report AI payback within 12 months; most say it takes 2–4 years.

Deloitte, 2025 survey

The Tokenomia View

The Synthesis

Activity ≠ Productivity. AI multiplies throughput; Tokenomia ensures it multiplies value.

check_circle

Verified attribution

Structural Shift

Beyond Raw Tokens and PR Counts

Legacy dashboards tell you how much AI you’re using. Tokenomia is built to tell you whether that usage is producing real value.

Typical Dashboards

Focus on vanity metrics: prompt counts, LOC, and Copilot adoption percentages.

Tokenomia

Aims to connect usage to outcomes: the conversations, topics, and shipped work behind the spend — not just the spend itself.

handshake

Co-design our pricing structure

We’re still setting pricing with our first customers — tell us your current spend in the form below and help shape it.

Inputs (Raw Data)

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Outcomes (Business Value)

Cost Avoidance +14%

$142.5k Net infrastructure save

Time to Value P95

-4.2 Days PR cycle time compression

insights TOKENOMIA INSIGHT

Illustrative example: an AI change in checkout reduced P99 latency without increasing code complexity.

Illustrative mockup — figures are examples of what Tokenomia could surface, not real customer results.

Deep Product Integration

Real Visibility for Engineering Leaders

Tokenomia Workstation — Attribution Flow

Live Sync: Production Mesh

Navigation

Active Workspace Core Platform Dev

Impact Analysis

Tracing commit outcomes vs LLM inference budgets

Range: Last 30 Days

Checkout Latency AI-Optimized SQL Layer

-220ms

Pre-AI Baseline: 480ms Optimized State: 260ms

Support Copilot Resolution Rate Analysis

82% +18% Deflection

Correlated with a 12% reduction in L2 escalation volume.

Engineering Outcome Score (EOS)

A composite metric of quality, speed, and business value.

92.4 / 100

Code maintainability 94%

Velocity impact 91%

Defect rate -24%

Illustrative mockup with fictional sample data — not a live customer dashboard.

Open the interactive demo ↗

Opens in a new tab · fictional sample data · no login required.

Limited to 25 teams for the initial Beta cohort.

Join the Early Access Cohort

Help us build the truth-telling engine for technical leaders.