Every instrument in the building is calibrated on a schedule. The minds interpreting the output are calibrated by nobody.
Sloane Labs is the capacity intelligence layer for research organisations. It reads recovery and cognitive load across research groups, laboratory teams and clinical programmes, forecasts where throughput and reproducibility will suffer, and acts before an experimental cycle is lost.
Reproducibility is treated as a methods problem. A meaningful share of it is a fatigue problem.
Protocol deviation, pipetting error and misread output are not random. They cluster in the back half of long sessions, at the end of consecutive late nights and around grant and submission deadlines. The clustering is measurable, and the timing is predictable in advance.
Research load is not smooth. Grant deadlines, submission windows, trial enrolment and instrument booking slots create sharp peaks that arrive on the calendar months ahead. They can be planned against rather than absorbed by whoever is nearest the bench.
Four places capacity turns into outcome
The long session
Sustained fine motor and attentional work degrades measurably across a long bench session, and further across consecutive late nights.
The interpretation
Fatigue narrows interpretation rather than slowing it.
The deadline sprint
Grant and submission sprints produce work that has to be redone.
The knowledge pipeline
When an experienced researcher leaves, the assay knowledge goes with them and the group loses months.
A grant cycle, read the way you read an instrument log
Group capacity across a submission cycle, with the forward projection that lets you reschedule bench time, add support or move an internal deadline before fidelity and throughput slip.
Select an operating state to redraw the forecast.
Normal bench and analysis rhythm, no deadline pressure. Recovery clears and capacity holds inside the tolerance band.
No intervention. The weekly brief confirms the group can absorb an additional workstream.
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.
What is actually running, not what is on a roadmap
Weekly capacity brief
A single page before the group meeting. Group capacity, what changed, the two teams to watch, and one recommended scheduling action.
Cohort capacity by group
Research groups, laboratory teams and clinical programmes reported as separate cohorts with trend lines across the year. No cohort renders below five people.
Forward risk alerts
When a group is forecast to cross a capacity threshold inside 72 hours, the alert fires with contributing factors and stated confidence.
Schedule simulation
Model a cycle before you commit. Move a run, shift an internal deadline or add support and see the projected capacity effect through to submission.
Individual agent, opt in only
Researchers who opt in get their own coach: recovery targets through a sprint, session timing guidance, answers grounded strictly in their own data. Nothing is visible to a supervisor.
Research culture evidence
An aggregated, anonymised record of how load was managed across the year. Useful for funder reporting, institutional review and staff representatives.
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 visible to a supervisor
Explicitly excluded from supervision, probation, tenure and disciplinary process. Given the power asymmetry in research, this exclusion is contractual and enforced 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 instrument is calibrated on a schedule. The minds reading the output are calibrated by nobody.
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.
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.
Baseline
Volunteers connect wearables and calendars. Individual baselines establish across a normal cycle and a peak one. No alerting yet, observation only.
Live briefing
Morning readiness briefs start reaching leadership. Forecast alerts switch on. Calibration against what the organisation already believes about its own load.
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
The questions we get asked first
Does it touch experimental or subject data?
Never. There is no connection to a LIMS, ELN, trial system or any research data store. Sloane reads consenting wearable signals plus calendar and booking metadata only.
Could a supervisor see an individual's data?
Architecturally, no. Individual physiology is never exposed; group leads see cohorts of five or more. Use in supervision, probation or tenure process is contractually prohibited.
Is this a wellbeing programme?
No. It is a research quality and throughput system. It measures capacity against the experimental and deadline calendar and changes decisions: session timing, support allocation and internal deadlines.
How does it fit institutional ethics review?
A DPIA template and a participant information sheet are supplied for review before any device is connected, with opt in consent, withdrawal rights and deletion on withdrawal built in.
What does integration require from IT?
OAuth for calendar and messaging, optional booking metadata, and individual device authorisation for wearables. No endpoint agents, no research system access.
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 group observed.
Calibrate the researchers, not just the instruments
A thirty minute conversation covering the architecture, the data boundary and what an eight week pilot would look like inside your programme.