Sloane Labs
SaaS and high growth technology

The system has observability on every service. The people keeping it up have observability on nothing.

Sloane Labs is the capacity intelligence layer for engineering organisations. It reads recovery and cognitive load across product, platform and on call rotations, forecasts where velocity and incident response will degrade, and acts before the sprint review or the pager tells you.

Read the research
p99
You track it for services, not for engineers
72h
Forward view on squad and on call readiness
5
Minimum cohort size in any report
0
Code, tickets or message content ever ingested
The practice, across a matter cycle
Live matters
14
Billable pressure
Peak
Recovery
Compressed
The thesis

Velocity is not a function of headcount. It is a function of how much of each engineer's week survives contact with the calendar.

You instrument every service to the percentile and page a human the moment a metric drifts. That human's own state, sleep debt, recovery, fragmentation of their week, is invisible to the same organisation that depends on it to resolve the incident.

Under a fixed hiring plan, you cannot out hire fatigue. The remaining lever is throughput per engineer per week, and that is governed by recovery, uninterrupted focus time and how on call load is distributed. All three are measurable and almost none of it is managed with data.

Where it costs you

Four places capacity turns into outcome

Incident response quality

The on call rotation

A night page does not cost one night.

Judgement narrowing

The architecture decision

Fatigue makes senior engineers narrower rather than slower.

Deep work throughput

The fragmented week

Focus time destroyed by meeting fragmentation is the largest and most controllable loss in most engineering organisations.

Institutional knowledge

The senior pipeline

When a staff engineer leaves, the context leaves with them.

Seen in practice

A release cycle, read the way you read your services

Squad readiness across a sprint and launch, with the forward projection that lets you rebalance the rotation, protect focus blocks or move a launch date before velocity and incident response degrade.

Select an operating state to redraw the forecast.

Squad readiness index
Sprint 1Sprint 2Code frzLaunchW+1W+2W+3

Normal sprint cadence, quiet pager. Recovery clears between weeks and readiness holds inside the tolerance band.

86
Squad readiness
18h/week
Focus time
Low
Forecast risk
Sloane acts

No intervention. The Monday brief confirms the squad can take on additional scope.

Signal model

What we read, and what each signal decides

A signal earns its place only if it changes an operational decision. Anything that does not is telemetry for its own sake.

Heart rate variability trend
Wearable, overnight · Daily
Whether an engineer is clearing load or accumulating it across a rotation.
Sleep duration, timing and regularity
Wearable, overnight · Daily
Recovery cost of night pages and readiness going into a launch week.
Calendar fragmentation
Calendar metadata only · Continuous
How much uninterrupted deep work survives the meeting load each week.
Out of hours communication load
Slack or Teams metadata · Continuous
Whether evenings are recovery or an unofficial second shift.
On call and page volume
Rotation metadata · Per rotation
Where pager load is concentrated and how it should be redistributed.
Release and launch calendar
Delivery metadata · Per cycle
Expected load spikes and where to hold capacity back ahead of them.
The product

What is actually running, not what is on a roadmap

Monday readiness brief

A single page before planning. Squad readiness, what changed over the weekend, the two squads to watch, and one recommended action.

Delivered to Slack, Teams or email

Cohort readiness by squad

Product, platform, infrastructure and support reported as separate cohorts with trend lines across the quarter. No cohort renders below five people.

Live dashboard, full history

Forward risk alerts

When a squad is forecast to cross a readiness threshold inside 72 hours, the alert fires with contributing factors and stated confidence.

Threshold alerts with stated confidence

Rotation and launch simulation

Model a plan before you commit. Split the rotation, move the freeze or protect focus blocks and see the projected effect on the squad.

What if runs against the real calendar

Individual agent, opt in only

Engineers who opt in get their own coach: recovery targets after a pager week, focus protection, answers grounded strictly in their own data. Nothing is visible to management.

Conversational agent, private by design

Retention evidence record

An aggregated, anonymised record of how load was distributed across squads and what interventions changed the trend.

Exportable, aggregate only
Data and governance

Reading human capacity only works if the boundary is unambiguous

Trust is the adoption constraint. These are commitments, written into the agreement, not preferences.

Never a productivity surveillance tool

No keystrokes, no commit counts, no ticket throughput per person. Excluded from performance review, calibration and disciplinary process, contractually and in the data model.

Opt in, always

No one is enrolled by default. Participation is individual, explicit and revocable at any time, with data deleted on withdrawal.

Five person minimum cohort

Aggregate views suppress any group smaller than five. Leadership sees cohorts, never a named individual's physiology.

Metadata, never content

Calendar and messaging integrations read timing, density and participant counts. Titles, bodies and message content are masked at ingestion and never stored.

Separated from selection

Contractually and architecturally excluded from selection, appraisal and disciplinary processes. That separation is written into the agreement.

UK GDPR and DPIA ready

Lawful basis, retention schedule, data subject rights and a pre drafted DPIA template supplied for your DPO before the first device is connected.

Every service has observability. The people keeping them up have none.

Design partnership

An eight week pilot with a defined exit

We take a small number of design partners per sector. A partner shapes the roadmap directly, gets preferential terms, and keeps the right to walk away at week eight with no obligation.

Weeks 1 to 2

Scope and governance

Agree cohorts, success measures and the data boundary. DPIA reviewed and signed. Integrations connected in a sandbox with a small internal group.

Weeks 3 to 4

Baseline

Volunteers connect wearables and calendars. Individual baselines establish across a normal cycle and a peak one. No alerting yet, observation only.

Weeks 5 to 6

Live briefing

Morning readiness briefs start reaching leadership. Forecast alerts switch on. Calibration against what the organisation already believes about its own load.

Weeks 7 to 8

Readout and decision

Joint review of accuracy, adoption and the decisions the signal changed. Written readout, roadmap input, and a clear go or no go.

What we need from you

  • One executive sponsor with authority over how work is scheduled
  • Twenty to fifty volunteers across two or three cohorts
  • Calendar and messaging integration approved by IT and the DPO
  • Two review sessions across the eight weeks

What you get

  • Full platform access for the pilot cohorts, configured to your operating calendar
  • Direct roadmap influence on capability specific to your sector
  • A written readout of accuracy, adoption and decisions changed
  • Preferential terms and first refusal on the sector in your market
For the technical and commercial buyer

The questions we get asked first

Is this developer productivity monitoring?

No, and it is deliberately architected so it cannot become that. Sloane never reads code, commits, tickets or keystrokes. It reads consenting wearable signals plus calendar and rotation metadata, and reports at cohort level only.

How is this different from DORA metrics?

DORA measures the output of the system. Sloane measures the state of the people producing it and forecasts where that state is heading, which is the leading indicator DORA cannot give you.

Will engineers accept it?

Adoption depends entirely on the boundary being real. Opt in, individual data never visible to management, cohorts of five minimum, and a private agent that works for the engineer. Teams that get this right see adoption above sixty percent.

What does integration require?

OAuth for calendar and messaging, optional on call rotation metadata, and individual device authorisation for wearables. No endpoint agents, no repository access, no network changes.

We already give people WHOOP or Oura. Why add this?

Those devices answer an individual question well. They do not join physiology to workload, aggregate to squads, forecast, or act. Sloane sits above whatever hardware you already deployed.

How do we know the signal is real?

Every score is deterministic and reproducible from versioned features, every forecast carries stated confidence, and the pilot readout compares prediction against what the organisation observed.

Give the humans the same observability as the services

A thirty minute conversation covering the architecture, the data boundary and what an eight week pilot would look like inside your engineering organisation.

Explore the platform
Opt in and anonymised Metadata only, never content