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Measure Your AI ROI

Engineering teams spend millions on AI tools but don't know what's actually working. Track AI adoption, token spend, and developer effectiveness in one platform.

The Problem

Your engineering team is drowning in AI tools. Multiple agents create a fragmented stack that's impossible to manage.

Token costs are skyrocketing with no visibility into ROI. You're spending thousands monthly without knowing which tools actually move the needle.

Performance reviews lack metrics. You can't identify which developers leverage AI effectively or who's just burning tokens on poor prompts.

Inefficient prompting is killing your ROI. Developers waste hours crafting prompts that generate subpar results.

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Solution

Finally understand which AI investments drive real engineering velocity with complete visibility into your AI stack.

Token ROI Analytics

Track every token spent across Copilot, ChatGPT, Claude, and custom models. See which tools deliver the highest ROI per dollar invested, with granular cost attribution down to individual developers and projects.

Developer AI Effectiveness

Identify your top AI power users and replicate their success patterns across the team. Measure code quality improvements, review time reduction, and deployment frequency gains from AI-assisted development.

Tool Consolidation Insights

Discover overlapping functionality between AI tools and eliminate redundant spending. Our analysis reveals which tools provide unique value versus expensive duplicates in your stack.

Prompt Optimization Guidance

Benchmark prompt effectiveness across your team and automatically suggest improvements. Reduce token waste by 40% while improving output quality through data-driven prompt engineering.

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How It Works

Get complete visibility into your AI investments in three simple steps. No complex setup, no vendor lock-in.

1

Connect Your Stack

Sync your AI tools and codebase in minutes. We integrate with GitHub, GitLab, Copilot, ChatGPT, Claude, and 20+ other AI services without disrupting your workflow.

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2

Track Every Token

Monitor spend, usage patterns, and code quality outcomes in real-time. Get alerts when costs spike and automatically identify your most (and least) effective AI workflows.

Engineering data analysis
3

Actionable Dashboards

Get executive-ready reports and team-level insights. Make data-driven decisions about tool renewals, training investments, and AI strategy with clear ROI metrics that engineering leaders trust.

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Early Access

Join engineering leaders who already know which developers are most effective at AI.

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Engineering leaders at top startups are asking which developers are most effective at AI. Get the data to answer that question.

Trusted by Engineering Teams

Engineering team collaboration
"Finally know which developers are actually effective with AI. Our token spend dropped 40% and code quality improved."
Sarah Chen, VP Engineering at TechCorp
Technical office collaboration
"The ROI tracking is game-changing. We cut our AI tool budget in half while improving developer productivity."
Marcus Rodriguez, CTO at StartupXYZ
Engineering team discussion
"Performance reviews now include AI effectiveness metrics. Makes conversations with developers much more productive."
Lisa Park, Engineering Manager at DevScale
Engineering team collaboration duplicate
"Finally know which developers are actually effective with AI. Our token spend dropped 40% and code quality improved."
Sarah Chen, VP Engineering at TechCorp
Technical office collaboration duplicate
"The ROI tracking is game-changing. We cut our AI tool budget in half while improving developer productivity."
Marcus Rodriguez, CTO at StartupXYZ