Customer layerAM stack

Client Lens

Every investor gets the letter written for them.

Personalised performance narratives, suitability-aware commentary and RM copilots that turn one house view into thousands of individually relevant client conversations.

1:1

Personalisation

Minutes

Quarter-end letters

Checked

Every outbound

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00Playable demo

Worked example

Quarterly letters — 8,400 investors

Client profiles + holdings + house view, across 3 jurisdictions

Clients

8,400 (retail, HNW, institutional)

Jurisdictions

UK, Ireland, Singapore

Portfolios

1,240 distinct model variants

Previous cycle

6 weeks, 14 writers

Run log

  1. Resolve the house view

    One approved house view; nothing in a letter may contradict it.

  2. Read each portfolio

    Actual holdings, actual returns, actual fees — per client, not per model.

  3. Write for the reader

    Same quarter, different letter: a retail client and a pension trustee get different explanations.

  4. Check suitability and tone

    Jurisdiction rules applied; every performance claim tied to the client's own numbers.

  5. Log for compliance

    Every letter, its evidence and its approvals stored as a suitability record.

Output

Press run to work this example end to end. Everything below is produced from the input above — sample data, real output shape: client letters, rm briefings, suitability log.

01What it does
01

Personal narrative

Performance explained against that client's own goals, entry points and risk profile.

02

RM copilot

Relationship managers get briefing packs and answer support before every call.

03

Suitability guardrails

Nothing leaves the building that the client's profile does not support.

02Inputs and outputs

Takes in

  • Client profiles
  • Holdings
  • House view

Hands back

  • Client letters
  • RM briefings
  • Suitability log