Executive Summary

Many knowledge workers, consultants, and professional services teams waste hours on manual time tracking or inaccurate recollection, creating billing disputes, lost billable hours, and weak productivity insights. The pain is acute for teams that need audit-ready records for invoicing, compliance, or coaching but don’t want to police screens or burden people with more manual entry. You could build a privacy-first, on-device multimodal AI that watches screen content and converts activity into a semantic timeline: task labels, concise summaries, timestamps, and exportable audit reports that sync with billing, project management, and coaching tools. The product would emphasize local inference on Apple Silicon (with opt-in cloud options), easy integrations, and simple controls for users and admins to accept or redact entries. This is an attractive market now: roughly 80 million knowledge workers × $120 ACV yields a $9.6B addressable market, and trends like better multimodal models, local inference, and hybrid work are increasing demand for accurate time visibility. Adoption drivers include billable-hour recovery, compliance needs, and team productivity programs. The clear competitive edge is semantic, context-aware timelines built with on-device privacy and robust export/integration capabilities, not just activity-level logs. Challenges are real—semantic accuracy, cross-platform coverage, user consent and legal/privacy regulation—but with 82/100 revenue potential and medium competition, a focused, privacy-first implementation is worth testing.

Market Opportunity

Automatic semantic timeline of work using screen-content AI targets a $9.6B = 80M knowledge workers × $120 ACV (annual subscription at $10/month) total addressable market with medium saturation and a year-over-year growth rate of 10% YoY growth in productivity and time-tracking software, driven by hybrid work and AI adoption (source: industry analyst synthesis).

Key trends driving demand: Multimodal AI is now capable of extracting semantic context from screen content — this enables products that convert raw activity into meaningful task logs.; On-device inference on Apple Silicon reduces privacy concerns and enables local-first AI features that users increasingly demand.; Remote and hybrid work models are increasing demand for accurate, audit-ready time visibility for billing, productivity coaching, and compliance.; Growing acceptance of personal analytics and quantified-work tools among freelancers and knowledge workers creates a direct consumer funnel for paid tools..

Key competitors include Timing, RescueTime, Toggl Track.

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Automatic semantic timeline of work using screen-content AI

Executive Summary

Market Validation

Market Opportunity

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