Redis Real-Time Decisioning Demo | Wealth Management Client Retention

Stage 1: The Architecture

Meridian-Style Wealth's Real-Time Decisioning Stack

Five tiers form a continuous loop: ingest, context, decide, act, learn. Redis turns portfolio data, held-away balances, behavior, and market context into an advisor-ready next best action. Systems of record stay where they are. Redis becomes the operational context layer that makes the moment actionable.

Data Sources

Portfolio Accounting Platform

Operational source

Salesforce FSC

Operational source

Risk Analytics Platform

Operational source

Market Data / News APIs

Operational source

Held-Away Aggregation API

Operational source

Kafka / Portal Events

Operational source

Ingest Layer

Redis Data Integration (RDI)

CDC from repositories and operational databases with sub-second activation

Redis Feature Form + Streams

Feature serving and live event hydration from Kafka, Redis Streams, and industry APIs

Unified Context Layer

Redis RAM

Hot portfolio state, live market signals, active risk alerts, and advisor workflow queue

Redis Flex

Warm portfolio and transaction history, relationship embeddings, held-away context, and prior engagement patterns

Feature Store

Churn risk, AUM at risk, product fit, and engagement propensity features

Redis Context Retriever

Assembles the Client 360 — portfolio state, relationship history, and risk context — and exposes it as structured MCP tools for the decision engine

Decision Engine

Eligibility Rules

Policy, compliance, and inventory constraints

NBA Ranker

Contextual ranking weighted by value, risk, and fit

Policy Arbitration

One action selected for the current moment

Output Channels (Act)

Advisor Workbench

Customer-facing activation surface

Client Portal

Customer-facing activation surface

Mobile App

Customer-facing activation surface

Compliance Archive

Customer-facing activation surface

↺

Learn: Decision logs and outcomes stream back into model training, policy updates, and the Redis context layer.

Pipeline latency

8.4 ms

Retention lift target

+15-25%

Wallet share opportunity

+$3.4M AUM

Stage 2: Trigger Event

Elena Petrov creates a decision moment

A private client logs into the portal during market stress hours before an advisor meeting. Turn drift signals into a ranked advisor playbook before the client meeting begins.

Live Trigger

Elena Petrov

$6.1M household | retirement in 24 months | advisor meeting at 9:00 AM

WEALTH

Eventportal_session_start

Customer surfaceAdvisor workbench

Decision objectiveRetention + wallet share

Decision windowBefore the surface finishes rendering

Context requiredHistory + live signals + policy

Business stakes+15-25%

Why This Moment Matters

Redis turns portfolio data, held-away balances, behavior, and market context into an advisor-ready next best action.

Without Redis: the application waits on siloed repositories and defaults to a generic next step.

With Redis: the decision surface opens with ranked, contextual action already staged for the moment.

Stage 3: Ingest

Industry repositories and streams flow into Redis

These are common repositories and streaming APIs for private wealth decisioning. They remain the systems of record. Redis activates the working set needed to decide now.

Redis Data Integration (RDI)Redis Feature Form

Source Systems → Redis

ADDE

Addepar / Tamarac

Common repository or streaming source for addepar context

→

SALE

Salesforce FSC

Common repository or streaming source for salesforce context

→

ALAD

Aladdin / Risk

Common repository or streaming source for aladdin context

→

LSEG

LSEG / FactSet APIs

Common repository or streaming source for lseg context

→

PLAI

Plaid / aggregation

Common repository or streaming source for plaid context

→

KAFK

Kafka / Redis Streams

Event streaming via Kafka or Redis Streams — no separate broker required with Redis Streams built-in

→

Ingest Pipeline Status

CDC modeReal-time

Streaming lag<100 ms

Feature parityTrain = serve

Custom sync code0 lines

Serving roleOperational context layer

Stage 4: Context Assembly

History and live state converge into one working view

Redis assembles profile history, account or household state, live intent, and policy constraints in one low-latency lookup path. What looked like a simple event in Stage 2 becomes a much richer decision moment here.

Redis RAMRedis FlexRedis Context Retriever

Historical Context

Customer value band512d ready

Tenure / relationship depthEstablished

Prior interaction patternKnown baseline available

Eligibility stateResolved in memory

Policy constraintsCurrent and active

Action historyFrequency caps enforced

Live Context

Current intentRetention + wallet share

Streaming signal stateFresh for this session

Capacity / inventoryAvailable

Risk / complianceWithin active rules

Surface readinessAdvisor workbench

Decision scopeProactive portfolio review

Key insight: Redis Context Retriever assembles the Client 360 — portfolio state, relationship history, and risk context — so the decision engine has exactly what it needs. The winning action becomes obvious only when historical context and live signals appear in the same response path.

Stage 5: Feature Serving

Online features hydrate the ranker in milliseconds

Redis Feature Form serves model-ready signals from Redis with train-serve parity. No fan-out calls to downstream systems during decisioning. No stale fallbacks.

Redis Feature FormRedis Feature Store

wallet_share_trend

Real-time feature served from Redis with train-serve parity.

down 18 pts0.3 ms

portal_anomaly_score

Model or ranking signal pulled online at decision time.

4.1 sigma0.4 ms

portfolio_drift

Real-time feature served from Redis with train-serve parity.

780 bps0.5 ms

household_embedding

Model or ranking signal pulled online at decision time.

512d ready0.6 ms

goal_proximity

Real-time feature served from Redis with train-serve parity.

24 months0.7 ms

concentration_risk

Risk and policy factor used to gate the action.

elevated0.8 ms

Feature Serving Performance

Features Hydrated

186

P99 Lookup Latency

<10ms

Train / Serve Parity

100%

Stage 6: Ranking

Candidate actions are ranked for this moment

Rules, policies, vector similarity, and business weighting combine to rank the best action now. The winner is selected because it fits the moment, not because it is the easiest generic fallback.

Redis SearchNBA RankerRules Engine

#1 Winner

PRIMARY ACTION

Proactive portfolio review

Lead with goal glide path and consolidation plan

NBA score0.94

#2 Candidate

ALTERNATIVE

Held-away consolidation pitch

Strong, but best presented after confidence is restored

NBA score0.79

Suppressed

POLICY

New alternative investment

Suppressed by suitability and current risk posture

Suppressed0.24

Stage 7: Business Impact

The value of choosing the right action now

Fast decisions matter, but the real value is choosing the right action while the moment is still open. Redis improves both latency and outcome quality.

Decision Economics

Pipeline latency8.4 ms

Retention lift target+15-25%

Wallet share opportunity+$3.4M AUM

The key insight: value compounds when the decision surface uses live operational context instead of generic fallback logic.

Moment Outcome

Generic

Siloed systems
lower relevance

→

Redis

Context-aware
higher impact

Stage 8: Outcome

Same surface. Different decision layer.

On the left is a generic or delayed path. On the right is the Redis-powered experience with ranked action already staged. Same customer moment. Different outcome.

Generic Experience

Elena Petrov

Private Wealth workflow

What the system knows

Partial profile, delayed retrieval, and limited live context.

Action shown

Held-away consolidation pitch

Outcome risk

The action fits broadly, but not the full moment.

Lower

relevance

Higher

fallback use

Siloed

context

Redis-Powered Experience

Elena Petrov

Decision-ready profile

#1 Next Best Action

Proactive portfolio review

Lead with goal glide path and consolidation plan

Why it wins

Combines history, live signals, business value, and active policy constraints in the same low-latency response.

Visible impact

Retention lift target: +15-25%.

High

relevance

Low

fallback use

Ready

before render

Stage 9: The Architecture, Proven

Architecture first. Architecture last. Outcome in the middle.

The same five tiers you saw at the start now tie directly to a measurable decision outcome. Common repositories and streaming APIs stay in place. Redis remains the operational decisioning layer that makes the customer moment work.

Data Sources

Portfolio Accounting Platform

Operational source

Salesforce FSC

Operational source

Risk Analytics Platform

Operational source

Market Data / News APIs

Operational source

Held-Away Aggregation API

Operational source

Kafka / Portal Events

Operational source

Ingest Layer

RDI

CDC and activation from systems of record

Streams + Features

Live event hydration and model parity

Unified Context Layer

Redis RAM

Hot portfolio state, live market signals, active risk alerts, and advisor workflow queue

Redis Flex

Warm portfolio and transaction history, relationship embeddings, held-away context, and prior engagement patterns

Feature Store

Churn risk, AUM at risk, product fit, and engagement propensity features

Redis Context Retriever

Assembles the Client 360 — portfolio state, relationship history, and risk context — and exposes it as structured MCP tools for the decision engine

Decision Engine

Rules

Eligibility, compliance, and policy

Ranker

Propensity, value, and fit

Arbitration

One action selected now

Output Channels

Advisor Workbench

Customer-facing activation surface

Client Portal

Customer-facing activation surface

Mobile App

Customer-facing activation surface

Compliance Archive

Customer-facing activation surface

↺

Learn: Outcomes feed retraining, policy updates, and future decisions without changing the systems of record.

Pipeline latency

8.4 ms

Retention lift target

+15-25%

Wallet share opportunity

+$3.4M AUM