WorkMonitor for software teams
Measure engineering without pretending lines of code are output
Deep work against fragmentation, capacity that catches the on-call tax, and a measure engineers will not route around, because a metric the team rejects gives you nothing to plan with.
Free for two seats, no card.
IT & software
What changes for an engineering org
Pick a line and the page it happens on opens on the right.
- AKMonitoring & AnalyticsA clear picture of the working week.Search or ask…
- Today
- Insights
- Activity board
- Live screens
- Team
- Agents
- Integrity
- App categories
- Reports & digests
- Capacity
Northlight StudioInsightsFocus, deep work and meeting load, week by weekFOCUS INDEX73/ 1002 vs last week0 = scattered · 100 = deep workHeadcount-weighted across 6 teams · Mon to Wed scoredFOCUS BY DAYweek avg 73707673————MonTueTodayThuFriSatSunWhat moved the indexDeep work +12%Meeting load −9%Idle and break time held flatTEAMFOCUS INDEXΔ WEEKHOURS- Product7824131h
- Design476172h
- Engineering14756262h
- Operations271235h
- Support9682168h
- Sales6643108h
776h captured so far this week, idle included · across 42 peopleWeek 36 to date
- Today
- Insights
- Activity board
- Live screens
- Team
- Agents
- Integrity
- App categories
- Reports & digests
- Capacity
- Product7824131h
- Design476172h
- Engineering14756262h
- Operations271235h
- Support9682168h
- Sales6643108h
Rollout
Introducing this to engineers without losing the room
- 1
Deny-list before you enable anything
Password managers, personal tooling, anything sensitive: excluded on the device before transmission. Leading with the exclusions is what makes the rest survivable.
- 2
Ship the self-view first
The VS Code companion gives an engineer their own view of their own week. A tool people can inspect is a tool people stop routing around.
- 3
Measure focus, not volume
Deep-work stretches, context switching and meeting density, not lines of code, which measures typing and rewards the wrong thing.
- 4
Wire it into what you already run
A typed v1 REST API, an OpenAPI spec, scoped keys and HMAC webhooks, so this becomes a source in your stack rather than another console.
Counting output vs. seeing how the work actually goes
workmonitor.vsEngineering metrics as usually sold
What gets measured
With WorkMonitor
Deep-work stretches, fragmentation and meeting density, with the score opening into its breakdown.
Engineering metrics as usually sold
Commits, lines, story points: proxies that reward splitting work up.
On-call and evenings
With WorkMonitor
Sustained evening drift as its own capacity signal, feeding a burnout warning.
Engineering metrics as usually sold
Invisible until it shows up as attrition.
Whether anyone uses it
With WorkMonitor
A self-view in the editor, per-app deny-lists, and a hash-chained log of who looked at their data.
Engineering metrics as usually sold
A tool imposed on the team that they cannot see into, and quietly work around.
Sensitive tooling
With WorkMonitor
Excluded on the device before transmission. Nothing to filter, nothing to leak.
Engineering metrics as usually sold
Captured, then filtered in a report, so it was still collected and still stored.
Integrating it
With WorkMonitor
Typed REST API, SDK, OpenAPI spec, scoped keys and signed webhooks.
Engineering metrics as usually sold
A nightly CSV, and a parser somebody has to maintain for ever.
Putting it in your own product
With WorkMonitor
Embeddable widgets, white-label branding and custom domains.
Engineering metrics as usually sold
Not an option; it is somebody else’s dashboard.
- Today
- Insights
- Activity board
- Live screens
- Team
- Agents
- Integrity
- App categories
- Reports & digests
- Capacity
- Product7824131h
- Design476172h
- Engineering14756262h
- Operations271235h
- Support9682168h
- Sales6643108h
What an engineering org gets to work with
- Productivity scoring (score, heatmap, category breakdown, rollups)
- Score explainability / breakdown
- App classification & category overrides + per-app privacy deny-list
- Focus & deep-work analysis
- Workload capacity signal (feeds AI Burnout Guardian)
- BI warehouse export (connector in Integrations)
Ask AI
Ask AI about engineering time
Answers grounded in focus, fragmentation and capacity signals, never in commit counts.
Pick a question above and WorkMonitor AI will answer from your team's real numbers.
- Today
- Insights
- Activity board
- Live screens
- Team
- Agents
- Integrity
- App categories
- Reports & digests
- Capacity
- AKAria K.Figma92Active
- JMJon M.Terminal78Active
- SDSara D.Slack61Active
- RPRavi P.Notion34Idle 11m
- LMLena M.Teams55In a call
- TVTomas V.Off shift0Off
The status meeting, already written
Status is normally assembled by asking. Here it is already: hours, activity, attendance and risk on one board, for one person or the whole company. Set the thresholds once and it tells you who needs you.
Jobs to be done
The jobs an engineering org runs here
- Score productivity & focusOne score per person, team or company, with the breakdown behind every one. Your categories rather than our defaults, and a capacity signal that names who is running hot.
- Manage remote & hybrid teamsOne live board across every zone, attendance in each person’s local day, capacity bands that name who is drowning, and a rollout that never touches a machine.
- Prove work with certificatesA finalized invoice mints a signed certificate the client checks for themselves. Selective disclosure proves the work without handing over the work.
- Monitor apps & websitesEvery app and site classified, every day replayable as a timeline. You see which tools are eating the week and which teams they are fragmenting.
Straight answers
The questions we would ask in your position
Every answer here is the one you would get on a call. Open as many as you like; they stay open, so two can be held side by side.
No. The signals here are focus, fragmentation and capacity, how much sustained attention the work got, and whether the people doing it are over their line. Output metrics like commits or tickets measure the shape of the tooling more than the shape of the work, which is why they are not what this scores.
Three things carry the rollout: the developer self-view, so the data reaches them first; per-app privacy deny-lists, so sensitive tooling never enters the record at all; and the explainability breakdown, so no number arrives without the activity behind it. The deployments that fail are the ones that arrive as a secret, and a metric the team rejects is a metric you cannot plan with.
It is a native agent with on-device processing and privacy rules applied before transmission. The help centre has the specifics on resource use per platform. MacOS is live, with Windows, Linux and a browser extension in beta.
Yes: a read-only v1 REST API with scoped keys, IP allow-listing and predictable rate limits, plus a warehouse export connector and Zapier for the no-code path. The full reference is published as OpenAPI.
Nearby
Teams with the same problem, from another angle
Take these with you
The software is the easy part of a rollout
Here is what we would send a manager doing one for the first time: how to read a productivity number, what to say to a remote team before anything is installed, and a policy you can adopt as written.
Point it at one team for a week.
Create the account, put the agent on a handful of desks, and leave it alone. On Friday you read the week instead of reconstructing it: hours against their projects, focus and idle per person, and the timesheets already filled in.
Free for two seats. No card, and no sales call to sit through.