AI productivity software with employee analytics

A per-employee coach that reads work patterns, wellness signals and output, then writes a plain-language report with a short action plan. The employee sees it first; managers get the summary.

Historical patterns become a forecast. Worktivity projects where a person's or a team's output is heading, so you can intervene in week two instead of week six.

Hours worked, break behavior, late-night sessions and streaks without recovery are scored into a burnout indicator, with an explanation of exactly what drove the score.

Every suggestion is tied to one person's own data: move deep work to the morning, cut the afternoon context switching, protect two no-meeting blocks a week.

The analysis runs continuously and publishes what changed, why it matters and what to do about it. No exports, no pivot tables, no weekly ritual.

The model learns what normal looks like in your organization, which is what makes the abnormal legible: a team whose focus time collapsed, a process that only works for half the group.

Optimization suggestions ranked by expected impact, so you can see which workflow change buys back the most hours and which team needs capacity first.

Start and finish times, peak hours, consistency and recovery mapped per person and per team, so schedules can be built around how people actually work.

Software that applies machine learning to employee work data to measure productivity, forecast trends and recommend changes. The difference from ordinary reporting is that it produces conclusions and predictions rather than charts you have to interpret.

The desktop agent records activity, app and website usage and working hours. Models learn the normal pattern for each person and team, then flag deviations, project trends and generate a written coach report with recommended actions.

No. Everything it produces is a recommendation with the supporting data attached. Promotion, performance and disciplinary decisions stay with managers, and employees can read the same report their manager sees.

Accuracy improves as the dataset grows, because the baseline shifts from a generic model to your organization's own patterns. Predictions come with the evidence behind them, so you can judge each one rather than trust it blindly.

It detects the measurable precursors: rising hours, shrinking breaks, late-night sessions and long stretches without recovery. That is a risk indicator rather than a diagnosis, and it is designed to prompt a conversation, not replace one.

Worktivity starts at $3.99 per user per month and the AI features are part of the platform rather than a separate add-on. There is a 14-day free trial and no card is required to start.

Knowledge-work sectors with enough data volume for a model to learn from: technology, consulting, agencies, financial services, healthcare administration and any organization already making decisions from data.

Data is encrypted in transit and at rest, access is role-scoped, and the platform is operated in line with GDPR. Employees can view their own analysis, which is part of running an AI layer people accept.