Build an accurate activity timeline by analyzing screen content

Build an accurate activity timeline by analyzing screen content targets a $5.0B = 100M knowledge-worker seats × $50 ARPU annually for semantic time & productivity tooling total addressable market with medium saturation and a year-over-year growth rate of 8% YoY — estimated growth for productivity and time-tracking SaaS driven by hybrid work and automation adoption (industry estimates for SaaS productivity tools 2022-2025)..

Key trends driving demand: Local and privacy-first AI inference adoption is increasing — this creates demand for tools that can run models on-device and promise data confidentiality.; Knowledge workers are frustrated with coarse app-level metrics — this drives interest in semantic, context-aware time reporting that maps directly to tasks and billing.; Improved vision-language models enable automatic summarization and labeling of screen content — this reduces the need for manual tagging and timers.; Rise of hybrid/remote work increases emphasis on asynchronous visibility and accountability — teams want automated timelines for retrospectives and billing..