Every AI dollar, and what it bought you.

Know exactly what you’re spending on AI tooling, how it maps to usage, and whether that investment is translating into real productivity gains.

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3.2×

Return on AI tooling spend

+31%

More PRs merged per engineer

−38%

Cost per merged PR, year on year

Multi-layered attribution

Weave uses a hierarchy of methods, so every AI contribution gets attributed.

Attribution method · falls back automatically

Verified · native API

Direct integration with tools like Cursor and Copilot. The strongest signal available.

Inferred · commit metadata

Git co-authorship on commits, for tools that expose no API.

Estimated · time-series inference

Modeled from activity windows. Directionally accurate, always labeled as estimated.

What usage tracks

Three signals that tell you not just what’s being used, but whether it’s working.

Foreground vs. Background AI

Usage categorized into foreground AI (interactive IDE assistants) and background AI (autonomous agents). Distinguish active pairing from automated assistance.

Sample data

Usage split · 30 days

62%

Foreground — interactive pairing

38%

Background — autonomous agents

What spend and ROI covers

Four signals that connect what you pay for AI to what you get back.

Subscription spend · monthly

Sample data

Tool

Seats

Monthly

Per seat

Cursor

120

$4,800

$40

Claude Code

$3,440

$40

Windsurf

$1,320

$30

Amazon Q

$600

$20

Total monthly

$10,160

Per-user cost attribution

Weave tracks per-user costs for Amazon Q, Claude Code, Cline, Cursor, Firebender, Sourcegraph, and Windsurf. For tools without per-user tracking, costs are calculated at the org level.

Cost tracking

Impact metrics

Usage patterns

Two kinds of AI contributor

Weave distinguishes between two fundamentally different categories of AI contributor.

Foreground AI

Interactive tools engineers use directly

Claude Code, Cursor, Windsurf, tools where an engineer is actively pairing with AI to write or review code.

Background AI

Autonomous agents working independently

Devin, Bugbot, CodeRabbit, agents that execute tasks, open PRs, and fix bugs without direct human involvement.

Autonomous task tracking

Multi-file refactoring, bug fixes, task completion.

ROI tracked separately

Cost and output measured against human-driven work.

Agent ROI and cost

Agent activity is tied to the same cost tracking and output metrics as human-driven AI. See the specific return on your autonomous agent stack.

Cost per merged PR

$412

$255

$156

Human

Foreground

Agents

MCP integration

Weave’s MCP server gives agents observability into your team’s health. Connected agents can query velocity metrics, drill into PRs, and align generated code with team standards.

How it works

No manual tracking. No spreadsheets built from memory at the end of the quarter.

Built for engineering and finance

Weave’s R&D Capitalization report identifies which development tasks qualify for capitalization by analyzing PR output, task association, and project data.

$3.7m

Qualifying R&D spend, year to date

Feature work

$1.9m

Platform

$1.2m

Maintenance

$0.6m

68%

Of development capitalizable

Capitalizable 68%

Operating 32%

Year-to-date

The report defaults to a year-to-date view, giving finance teams a consistent snapshot of development activity across the fiscal period.

Team, repo, or project

Break the report down by whichever unit your finance team files against.

Slice capitalization data precisely so the numbers accurately reflect the specific work being performed. Pairs with Jira or Linear for the most accurate results.