Hidden Labs
Measured outcomes

Predict. Measure. Prove.
Each stage personalised per individual.

Behavioural forecast880 models
Revenge entrySame instrument · repeated ×4
−$1,24091% risk
Position sizingAbove session limit
−$68074% risk
Loss chasingAfter two red trades
−$41062% risk
Prediction

Patterns found before live session

A behavioural portrait is built from imported history - each pattern and its cost known up front.

Live sessionLive
Frequency alert3 entries in 4 minutes
14:32Acknowledged
Pattern match4th re-entry, same direction
14:36Ignored
Stop violationMoved twice this session
13:52Flagged
Measurement

Tracked live, alongside each individual

The model runs in real time through every session.
Every detection and response recorded as it happens.

Predicted vs actual94% accuracy
19 May sessionRevenge cluster, flagged
−$918pred −$920
18 May sessionClean, unflagged
+$340pred +$355
17 May sessionOne intervention
−$120pred −$110
Proof

Predicted versus actual, cost avoided

Unflagged decisions stay profitable - flagged behaviours explain the difference. Auditable from day one.

For the provider

Protect client capital,
Extend client tenure.
Grow lifetime value.

Reduce preventable attritionReduce Attrition

Early attrition converts acquisition expenditure into unrecovered cost and forfeits all future revenue from the account. The system surfaces the behavioural patterns that precede account closure before they complete.

Improve return on acquisition costImprove Acquisition Cost

Acquisition is only recovered if the account survives long enough to mature. Extending the productive life of each client raises the return on every dollar spent winning them.

Greater retention, higher lifetime valueGreater Retention

Clients who avoid catastrophic sessions stay active longer and trade with more consistency - compounding into materially higher lifetime value across the book.

Supervisory evidence, built inCompliance Evidence

Every observation and intervention is logged as defensible, auditable evidence - demonstrating proactive duty of care without adding to the supervisory workload.

The desk manager view

The desk manager monitors every participant independently,  
Risk surfaced across the desk as it forms.

Each participant carries their own portrait.
The manager sees the whole desk at once, without losing the individual underneath.

Scroll to walk through three active cases.

MC
M. Chen CASE-0041
Giveback-prone · 1,204 decisions
Alert
This session
Cascade · 5 flags · matches 3 prior
Detections
09:42GivebackPeak +$2,340 · down $400
11:08RevengeSame direction, 6 min after loss
12:18Duration14 sec trade · avg 3m 12s
13:24Streak4 consecutive losses
14:15Oversize3× baseline contract size
This is the fourth time Chen has entered this sequence. The previous three ended in their worst session losses. Five warnings sent across the session, none acted on.

Sample case · static preview

Hidden Labs Desk
Sample desk
Supervisory surface

Behavioural risk becomes visible,
While it is still forming.

Detections become cases. Cases carry timestamped evidence.  
The layer that protects the individual is the same layer that demonstrates supervision.

Compliance Board 15 open
Sample board
Every detection logged · Every state change timestamped · Every owner assignment recorded SLA · 24h response on flagged
Compliance Board 15 open Sample board
6Monitored
3Flagged
2Review
4Closed
MC
M. Chen CASE-0041
Giveback cascade · Under review
HIGH

Fourth giveback cascade in five sessions. Alerts ignored nine times across the last four sessions. Recommending intraday throttle and post-session review.

Owner C. Reyes Opened 19m ago Starred · Escalated
Every detection logged · Every state change timestamped · 24h SLA on flagged