Real-Time Employee Productivity Tracker
Budget / SalaryHourly project
TypeFreelance project
LocationRemote
Posted1 hour ago
I need a solution that streams live data on the applications each employee actively uses during work hours and turns that information into clear productivity insights. The goal is to measure work performance and productivity only; attendance, internet blocking, keystroke capture, mouse movement, or screenshots are not required.
What I expect:
• A lightweight desktop agent (Windows first, macOS a plus) that quietly records foreground application name, window title, start-stop times, and idle thresholds, then pushes that data to a secure central store.
• A web dashboard that updates within a minute, lets me filter by user, team, date, or app, and exports reports to CSV.
• Role-based access so managers see only their teams.
• An installer, admin guide, and clean hand-over of source code and build instructions.
Acceptance criteria
1. Agent stays under 2 % average CPU.
2. Activity reaches the dashboard in under 60 seconds.
3. Reports are downloadable for any custom date range.
PostgreSQL and AWS are already in place here, so solutions that plug into those will move faster, but I am open to your preferred stack—Electron, .NET, Python, or another language—as long as it meets the performance targets.
Send a brief architecture outline, any similar work you have done, and the timeline you would need for both an MVP and the final polished release.
What I expect:
• A lightweight desktop agent (Windows first, macOS a plus) that quietly records foreground application name, window title, start-stop times, and idle thresholds, then pushes that data to a secure central store.
• A web dashboard that updates within a minute, lets me filter by user, team, date, or app, and exports reports to CSV.
• Role-based access so managers see only their teams.
• An installer, admin guide, and clean hand-over of source code and build instructions.
Acceptance criteria
1. Agent stays under 2 % average CPU.
2. Activity reaches the dashboard in under 60 seconds.
3. Reports are downloadable for any custom date range.
PostgreSQL and AWS are already in place here, so solutions that plug into those will move faster, but I am open to your preferred stack—Electron, .NET, Python, or another language—as long as it meets the performance targets.
Send a brief architecture outline, any similar work you have done, and the timeline you would need for both an MVP and the final polished release.
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