The measurement layer for enterprise AI — prove ROI across humans and agents
Larridin is the measurement layer for enterprise AI: see what AI costs across your organization, what your teams (human and agent) produce with it, and which workflows to automate next. The platform covers AI adoption tracking, AI fluency assessment, AI impact analysis, workflow intelligence, developer intelligence and spend intelligence — the full "prove the ROI" stack. The credibility markers are unusually strong for this category: $17M+ raised, backed by Andreessen Horowitz, Gradient and Bloomberg Beta, with an a16z podcast feature.
Who it's for: enterprise AI leads and CTO offices under pressure to justify AI investments with numbers rather than vibes, finance teams needing AI spend visibility, and platform teams deciding which workflows to automate next based on measured impact rather than hype. The category is arriving fast as the "AI everywhere" phase matures into the "show me the returns" phase. Enterprise demo-driven sales; the evaluation should center on whether its measurement definitions (productivity attribution, agent output value) hold up to finance-grade scrutiny.
What it is
The measurement layer for enterprise AI — prove ROI across humans and agents
Pricing
Paid
Primary category
Productivity
Source code
Closed source / hosted
Larridin is one of many tools in its category. Before committing to it, weigh a few practical points that tend to decide whether a tool actually fits your work:
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