Minimal-effort field time capture that syncs job hours to payroll

Field service and trades-based small businesses—plumbers, HVAC, landscapers—struggle to capture accurate field hours and reliably push those hours into payroll and job-costing systems, creating payroll errors, billing disputes, and opaque job margins. There are roughly 20 million service SMBs whose combined annual spend on payroll/time/job-costing is about $30 billion, and many still rely on manual timesheets, call-ins, or error-prone punch clocks. You could build a mobile-first, minimal-effort time-capture system that combines passive sensor signals and lightweight ML to infer job start/stop and classify drive versus work time, surfacing only a single weekly confirmation tap for technicians. That product would include secure, two-way API integrations to major payroll and job-costing platforms, configurable business rules and approval workflows, and an auditable sync so payroll teams can reconcile and correct before funds move. Pricing could target the $1,000–$2,000 ACV range per SMB (aligning with the assumed $1,500 combined spend) or per-user tiers, with pilots designed to prove time savings within 30–60 days. This market is attractive now because near-universal smartphone adoption, accessible payroll APIs, and improved ML inference meaningfully lower the friction and cost of deployment, supporting a large $30B addressable spend. To stand out you must deliver demonstrably higher accuracy and lower technician burden than incumbents, invest in privacy and battery-friendly sensing, and offer fast, turnkey integrations and change-management support—challenges that are solvable but require disciplined engineering and channel partnerships.