Instantly analyze text inputs to detect irregularities and stop fraudulent behavior in real time.
CELEBRUS DATA PLATFORM
Celebrus fastText
We have embedded the leading language library fastText into the product to enable out-of-the-box functionality for real-time text analytics.
Capture real-time customer insights across your digital channels.
A large proportion of customer interactions on your digital channels are text-based. When leveraged correctly, these can form valuable data and customer insights.
Celebrus enables organizations to run text analytics models in real-time scoring environments, leveraging our tried and tested connectors to Microsoft Azure Machine Learning Studio and Openscoring Server. The machine learning model running in these real-time environments can be easily and quickly connected to the fastText library to train the model with no additional configuration effort required.
Enrich customer profiles with real-time semantic analysis.

Enriched customer profiles
Natural Language Processing capabilities enable out-of-the-box functionality for real-time text analytics.

Instant fraud prevention

Smarter personalization
Stay relevant and deliver hyper-personalized messages that resonate based on real-time customer behavior.
Determine sentiment and identify opportunities or threats for instant action.
Capture everything related to visitor behavior and experience, including text inputs on any channel and device.
Tag-free
Data scoring
Granular detail
Structured data

Explore related features
Sense and trace
Uncover compromised accounts and trigger alarms to respond to fraud instantly.
Marketing signals
Transparent scoring for customer behaviors based on interest and intent.
Anomaly detection
AI and machine learning to detect hidden data patterns to catch and prevent fraud.
Instantly capture and analyze text inputs on any channel and device.
Powerful enrichments based on the text a customer inputs not only improves the view an organization has of their customer, but also enables a wide range of new use cases.