Model your return
before you commit.

Built for VPs of Engineering who need to walk into a budget meeting with real numbers. Adjust the inputs below — the model updates in real time.

Tell us about
your org

10 50 500+
$80K $180,000 $350K
$0 $7,000 $50K
5% 30% 100%
0% 15% 40%

Full observability + ROI measurement. Typical 6–8 week deployment.

Model uses industry benchmarks: 2.3x velocity uplift at Correlate, 4.1x at Compound. Knowledge retention valued at 1.5x annual salary per departing developer. Grafter deployment included in Enterprise ROI.
Estimated annual ROI
14x
$2.3M net value on $168K investment
AI tooling cost (annual) $84,000 current spend
CodeVine platform est. $84,000 token-based, usage dependent
Velocity uplift value $2.07M 2.3x on 30% active devs
Knowledge retention value $405K 7 departing devs × $180K
Value across the maturity curve your current stage highlighted
Capture
$420K
Correlate
$2.3M
Compound
$5.8M
Estimated payback period 3 weeks
Skills to capture in year 1 ~47
Shadow AI cost (est.) $31K/yr

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How we calculate the numbers

Velocity uplift

Based on GitHub's 2024 Copilot research (55% faster task completion) and internal Grafter deployment data. We apply a conservative 2.3x multiplier at Correlate stage, 4.1x at Compound, applied only to the percentage of developers actively using AI tooling.

Knowledge retention

Valued at 1.5x annual salary per departing developer — the industry standard for replacement cost (recruiting + ramp time + institutional knowledge loss). Applied to the AI-specific knowledge portion, estimated at 30% of total institutional value for actively agentic engineers.

Shadow AI cost

Estimated based on average unmanaged API key spend observed across enterprise deployments — typically 25–40% of developers using personal or unapproved AI tooling, spending $80–150/month without visibility or policy enforcement.

Platform cost estimate

CodeVine's token-based pricing means your platform cost scales with actual usage. The estimate shown uses average token consumption patterns from current deployments — exact pricing varies based on your LLM provider mix and usage patterns. Talk to us for a precise quote.

This calculator provides estimates based on industry benchmarks and CodeVine deployment data. Actual results vary based on team composition, tooling adoption, and engagement model. All figures are annual unless otherwise noted.

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