Know every trader.
See risk across your platform.

Cooper’s AI learns each trader’s behaviour, recognises developing patterns
and gives your team an earlier view of who needs attention and why.

Explore the desk manager view

DESK MANAGER VIEW · LIVE WALKTHROUGH · SAMPLE DATADESK MANAGER VIEW · SAMPLE DATA

Cooper · Trading intelligenceILLUSTRATIVE DATA
Desk manager dashboard showing a developing behavioural sequence and the evidence for review.

Dashboard preview · Explore the interactive view on desktop.

A living portrait.
Built over every session.

Cooper builds a continuously updated model of behaviour under pressure from that trader’s own history.

Each session sharpens the signal. Repeating sequences become clearer over time.

INDIVIDUAL HISTORY

One trader.
Their own
baseline.

Behaviour understood
across their sessions.

Frequency

The pace and duration
of their usual activity.

Position sizing

How their exposure changes
as the session develops.

Response after loss

What they tend to do next,
and how that changes.

SESSION WALKTHROUGH · SAMPLE DATA

Recognise the
sequence earlier.

Changes in timing, activity and size can form a developing sequence. Each observation gains meaning from what came before.

Cooper connects that sequence with earlier outcomes, then keeps the team’s response and the eventual result in the record.

A developing pattern. A clear case for review.

  1. Detect

    A change against that trader’s own history.

  2. Connect

    Related observations build the evidence.

  3. Review

    Your team sees what needs attention and why.

  4. Record

    The response stays linked to the case.

A clear read.
Evidence behind it.

Ask why a trader was flagged, how their own history supports the read and what deserves a closer look.

Cooper explains the developing pattern in the context of the individual and the market. Your team decides how to respond.

Choose a question to try the conversation.

Cooper

Your read of the desk

WATCHING
M. CHEN5 detections · this session

Cooper

I’d review Chen’s session first.

Five changes are forming a familiar sequence.
The pattern has appeared in three earlier sessions.

Why Chen first?

Cooper

Five changes are developing together: giveback, re-entry after a loss, shorter holds, consecutive losses and larger size. The three earlier sessions with this sequence ended among Chen’s largest losses. That history is a reason to review today’s session, not a certain outcome.

Scripted concept · Cooper recommends. Your team acts.

Fits alongside your existing platform.

Cooper reads executions, positions and session context to surface behavioural patterns for your desk.

Bring the evidence into your team’s existing workflow. Your team decides how to respond.

YOUR EXISTING DATA · CONNECTED TO YOUR TEAM

  • Executions

    Entries, exits and timing.

  • Positions

    Size and exposure.

  • Session context

    The market around them.

Cooper

Individual patterns.
Developing risk.

OBSERVATIONS & EVIDENCE

Your team

Review, respond and
record the outcome.

Decisions and actions stay with your team.

Predict. Measure. Prove.

Connect the earlier warning, your team’s response and what happened next.

  1. 01Predict

    Recognise the risk earlier.

    Learn each trader’s recurring patterns and forecast where a developing sequence may lead.

  2. 02Measure

    Record what your team did.

    Link each warning to the review, response and timing. Keep the evidence in one record.

  3. 03Prove

    Compare with what followed.

    Compare predicted and observed outcomes. Track whether behaviour changes over later sessions.

Illustrative workflow · Each trader measured against their own history.

See what your trading history reveals.

Explore individual behaviour, developing patterns and
the evidence behind Cooper’s read of your trading population.

Discuss a private data study
Cooper · Sample profile
Hidden LabsCOOPER · BEHAVIOURAL PROFILESAMPLE DATA

A. Novak

10 April–20 May 2026 · Trading behaviour

Developing profile
142Trades analysed
24Sessions reviewed
5.6Usual trades / session
6Profile snapshots

01 · COOPER’S READ

Activity often continues beyond the usual session.

The supplied history contains repeated changes in trading frequency, re-entry after losses and continued activity during deteriorating sessions. Cooper compares those patterns with Novak’s own baseline.

Cooper

Start with the sessions where activity expanded. Then review the sequence around losses. A re-entry alone is not enough to raise a flag: this history also contains adaptive responses.

02 · PATTERNS IN THE HISTORY

Three recurring patterns to review.

Sessions containing each pattern, out of 24 analysed. These counts overlap.

Activity beyond usual23 of 24 sessions
Re-entry after a loss17 of 24 sessions
Continued trading through losses11 of 24 sessions
10 adaptive re-entriesThe supplied example identifies these post-loss entries as adaptive. They stay separate from the flagged re-entry pattern.

03 · ESTIMATED CONTRIBUTION

Separate the observed result from the modelled comparison.

The sample compares the recorded result with an estimated result after removing the identified behavioural patterns.

Recorded result−$4,682.50Observed across 24 sessions
Modelled comparison−$1,840.00Estimated with patterns removed
Estimated difference$2,842.50Recorded vs modelled result

This difference is an estimate, not measured savings or proof of what would have happened.

04 · WHAT COOPER WATCHES NEXT

The next session can change the read.

Frequency

Does activity return towards the trader’s usual session rhythm?

Response after losses

Does the same sequence recur, or does the trader respond differently?

Observed outcome

Record what followed, then update the profile as new evidence arrives.

HIDDEN LABS · COOPER

Let’s talk.

Tell us about your team and what you’d like to explore.

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