Employee Productivity & Workforce Analytics Platform

Most organisations can tell you what a team delivered, but very little about how the working day was actually spent. This platform was designed to answer that question with structured data instead of guesswork.

It collects activity signals from managed endpoints, normalises them, and presents them in a centralised administrator dashboard: what applications were open, which websites were visited, how much time was genuinely active, and where the day went.

Without a shared view of workload, managers rely on check-ins and self-reporting. That is slow, inconsistent, and impossible to scale across shifts, departments or remote teams.

The design problem was to make activity data legible at three altitudes at once: an organisation-level overview, a team-level trend, and an individual timeline that a manager can actually read.

Data model

• Employee, team and device records
• Activity sessions with active and idle classification
• Application usage intervals
• Website activity records
• Screenshot capture events with retention windows
• Aggregated daily, weekly and monthly rollups

Administrator dashboard

• Workforce overview with productivity trends
• Employee-level drill-down with an activity timeline
• Application and website usage breakdowns
• Daily, weekly and monthly summary views
• Filters by employee, team, date range and device
• Exportable reports for internal review

// Activity is normalised into sessions before it is aggregated.
$session = ActivitySession::open($employee, $device, $startedAt);

$session->recordAppUsage($processName, $windowStart, $windowEnd);
$session->recordSiteVisit($host, $openedAt, $closedAt);
$session->classify($activeSeconds, $idleSeconds);

// Rollups are rebuilt on a schedule so dashboards stay fast.
DailySummary::rebuildFor($employee, $date);

• Activity data is noisy — idle detection has to distinguish a long read from an abandoned desk.
• Volume grows quickly: per-minute sampling across a workforce needs aggregation before it reaches the dashboard.
• Screenshots raise a privacy question that pure telemetry does not, so retention and visibility had to be explicit design decisions.
• Reporting has to stay readable when an employee has thousands of events in a single week.

The interface is deliberately framed around workforce analytics and employee activity insight: aggregate trends first, individual detail on demand, and clear retention rules for the most sensitive data type on the platform.

In progress. Public metrics are not available while the platform is under active development, and no performance or productivity numbers are claimed here.