CUSTOMER STATE
Build a governed, useful view of the customer from behavioural, transactional and operational data.
Fuse × Databricks / Data + AI
CUSTOMER DATA
SHOULD DO
SOMETHING.
The lakehouse should not end at the dashboard. It should change the next customer decision.
Fuse connects Databricks to the customer experience. We help brands turn governed customer data into intelligence, models, decisions and activation, then feed the outcome back into the system.
DATA
Governed customer state
AI
Intelligence + models
DECIDE
Next best action
ACT
Braze + channels
01 / The opportunity
THE DATA PLATFORM IS BECOMING A CUSTOMER PLATFORM.
Customer 360, identity, AI, modelling, audience intelligence and decisioning are moving closer to the governed data foundation. For Fuse, that changes the centre of gravity. The opportunity is bigger than implementing another marketing tool. It is helping clients build the intelligence layer that decides what every downstream customer system should do.
02 / The customer loop
From signal
to action.
Back again.
INTELLIGENCE
Turn that state into propensity, churn, value, recommendations, audiences and business-ready insight.
DECISIONING
Use live context, models and AI to decide what should happen next, rather than simply describing what happened.
ACTIVATION
Move the right decisions into Braze and other execution channels, then return performance signals to the lakehouse.
03 / Fuse × Databricks
THE BRIDGE BETWEEN INTELLIGENCE AND EXPERIENCE.
Fuse sits in the useful gap between data teams and customer teams. We understand the governed data layer, and we understand what has to happen downstream for that intelligence to become a customer experience.
01
Customer 360
Unify customer state around the governed data foundation instead of creating another disconnected copy.
02
Databricks → Braze
Design CDI, API and activation patterns that keep intelligence close to the data and execution close to the customer.
03
Models & intelligence
Recommendations, churn, lapse, propensity, RFM, lifetime value and other decisioning signals.
04
Data architecture
Schema, payload, identity, consent and attribute design built for downstream customer engagement.
05
Closed-loop measurement
Return campaign and behavioural outcomes to the lakehouse so the system learns from what actually happened.
06
Agentic customer engagement
Create the governed context and operating layer required for AI agents to reason and act safely across customer journeys.
04 / Databricks + Braze
USE EACH PLATFORM FOR WHAT IT DOES BEST.
Our working architecture is simple: Databricks holds customer state and intelligence. Braze composes audiences, orchestrates journeys and activates experiences. Decisions and outcomes move between them rather than forcing either platform to become the other.
Customer state
+ intelligence
+ intelligence
Data · identity · models · propensity · recommendations · consent · decision context
FUSE
↔
↔
Orchestration
+ activation
+ activation
Audience composition · journeys · channels · personalisation · experimentation · execution
05 / In the field
Architecture that ships.
Irish National Lottery / 2026
Databricks → Braze.
One customer view.
Fuse designed a Databricks-to-Braze architecture around customer state, consent and activation, including payload design and the return of operational states to the lakehouse. The principle is more important than the diagram: keep the customer truth governed, then make it useful at the point of engagement.
Greenfield architecture
Choose the foundation before you inherit the constraints.
Fuse advises clients across Databricks, Fabric and Snowflake rather than forcing a platform decision. The question is which foundation best fits the organisation, the customer use cases and the speed at which value needs to reach production.
06 / What comes next
DATA → CONTEXT → DECISION → AGENT → ACTION.
Databricks is moving rapidly into Customer 360, AI-assisted profile creation, audience building and agentic campaign workflows. Fuse's opportunity is to help clients make that transition real: governed customer context underneath, clear decision ownership in the middle, and execution systems connected at the edge.
07 / Databricks FAQ
What does Fuse do with Databricks?
Fuse helps customer, marketing and data teams use Databricks as a customer intelligence and decisioning foundation. We design customer data architecture, Customer 360, modelling, Databricks-to-Braze activation, measurement and emerging agentic customer engagement use cases.
How do Databricks and Braze work together?
Fuse typically treats Databricks as the governed customer state and intelligence layer, while Braze provides audience composition, orchestration and customer-facing activation. The exact ownership depends on the client's architecture and use case.
Can Fuse help choose between Databricks, Snowflake, Fabric or another data platform?
Yes. Fuse has worked on greenfield customer-data projects across Databricks, Microsoft Fabric and Snowflake and can help teams assess the architecture against their existing skills, cost model, speed to proof of value and activation requirements.
Is Fuse a Databricks partner?
Yes. Fuse is a Databricks partner focused particularly on the point where customer data, AI, decisioning and customer engagement meet.
08 / Build the intelligence layer
MAKE CUSTOMER DATA
DO SOMETHING.
Talk to Fuse →Data / intelligence / AI / activation