How Gauzy Turns Work Into Evidence
This chapter follows how Ever Gauzy turns a person’s work into records that can be reviewed, reported, and—when the organization chooses—connected to billing. The focus is the difference between a time interval, a detailed activity signal, a timesheet, and a derived report. That distinction gives readers a practical way to judge what Gauzy has actually observed, what it has calculated, and what remains an interpretation about performance or value.
One work session, several kinds of record
A timer produces a deceptively simple question: how long did someone work? Gauzy’s data model breaks that question into several related records because duration, activity, review, and billing serve different purposes.
A time log is the broad interval. It records when work started and stopped, whether the interval is tracked or manual, where it came from, whether it is billable, whether it is still running, and any description or reason attached to it. It belongs to an employee and can point to a timesheet, project, task, client, team, and one or more smaller time slots. This is the record most closely associated with “the person spent this interval on this work.”
A time slot supplies a finer-grained activity window. It records duration and activity measures such as keyboard and mouse interaction counts, movement or location signals, and an overall activity value. It can hold raw or custom activity data and owns more detailed activity records, screenshots, minute records, and tracking sessions. Its relationship to time logs is important: a time log can describe the business interval, while time slots describe evidence collected during portions of that interval.
An activity record describes something observed within a slot. It can have a title, description, metadata, date, time, duration, source, and recording timestamp, and it can be connected to the employee, project, task, and time slot. In a practical scenario, the time log might say that an employee tracked two hours on a website project, while activity records provide a more detailed account of what applications or work contexts appeared during that period.
A screenshot is another optional evidence type, not a synonym for activity. Gauzy stores a file and optional thumbnail reference, recording time, and storage-provider information. The model also allows fields indicating whether an image is work-related and which applications it contains. Those fields can support review or analysis, but they do not make a screenshot an objective verdict about the person’s work.
Custom tracking introduces a session layer. A session has an identifier, a start time, and a last-activity time, and it can span multiple time slots. The custom tracking service can retrieve the session payloads associated with a time slot, either as encoded data or with decoded data when that is requested. This gives an extension or specialized tracker a place to submit richer signals without changing the meaning of every ordinary time log.
A timesheet is a review and aggregation boundary. It stores duration and activity totals, start and stop dates, and states such as pending, submitted, approved, or locked. It records submission, approval, and locking times, the approving user, and whether the work has been billed. A timesheet is therefore not just another timer view. It is where an organization can treat captured work as a governed record before it becomes part of a financial or management process.