The ACCELERAID Platform
One platform.
Data, AI and automation
for regulated industries
From data enrichment and AI scoring to automated campaigns and management reporting. ACCELERAID connects your data sources and makes AI usable in daily operations.
Platform overview
How the platform is structured
Five modules on three levels, plus three cross-module building blocks. Each module can be used on its own or combined with the others.
The shared data foundation for all modules.
Context and predictions for every decision.
Delivered through campaigns, website and app, and assistants.
Module · Layer 01 Data
Customer Data Platform (CDP) & Data Governance
Customer, transaction and operational data in one central system of record – with consent and access control.
Cross-module · between data and intelligence
AI Context Layer
Shared context for AI: identity, consent and the meaning of data.
In development: agentic AI – specialist agents that act within defined rules and under human control.
Module · Layer 02 Intelligence
Prediction Engine
Propensity and churn scores, next best action and decision rules – in real time or in batch.
Cross-module · between intelligence and applications
Customer Lifecycle & Value Management (CLM/CVM)
Journeys for each lifecycle phase – from onboarding to win-back.
Module · Layer 03 Applications
Trigger & Campaign Automation
The mechanics behind the journeys: triggers, rules, channels and measurement.
Module · Layer 03 Applications
Experience Optimisation & Personalisation
A/B and multivariate testing, personalised landing pages and application journeys.
Module · Layer 03 Applications
AI Assistants & GenAI Enablement
Assistants for customers and teams built on your company knowledge – with PII filtering before the LLM call.
Cross-module · across all layers
Reporting & Data Governance
Configurable dashboards, data quality scores per source and a consent overview per channel.
For all modules
Applies regardless of which modules you use.
One data model
Customer, account, transaction and campaign data sit in one shared data model.
Scores with reasons
Every prediction shows the features that drove it.
Consent and access rights
Maintained once and applied to every module and every channel.
Integrations
Connects to your existing infrastructure
Data flows in from core banking, card processing, CRM and the data warehouse. Results flow back into your systems and out to your channels – email, app, website, SMS and the advisor cockpit.
Read on
Where to go next.
From the blog
Data & Technology
AI Context Layer in Banking: What a Banking Agent May Remember and What It Must Forget
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Insights in a Silo: Why Banks Have Enough Data but Do Too Little With It
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