WhatAn analytics tool that identifies low-value, performative, or redundant work within organizations by analyzing communication patterns, ticket flows, and meeting loads.
SignalMultiple commenters express frustration that even when companies have excess capacity they fill time with meaningless work rather than reducing hours — there is a deep sense that much corporate activity is waste that nobody has tools to quantify or eliminate.
Why NowLLMs can now parse unstructured work artifacts (Slack threads, Jira tickets, meeting transcripts, docs) at scale, making it feasible to programmatically identify low-signal work for the first time.
MarketCOOs and VPs of Engineering at companies with 200+ employees; adjacent to the $10B+ business intelligence market; Jellyfish and LinearB track engineering metrics but none explicitly surface and score work by value-add.
MoatTraining data from real organizational patterns creates increasingly accurate waste-detection models that are hard to replicate without similar deployment breadth.
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