Litify
The legal operating system built on Salesforce for high-growth firms and corporate departments.
Enterprise-grade predictive analytics for hyper-personalized customer lifecycle management.
Nuevora, now an integral division of Sutherland, represents a sophisticated AI-driven predictive analytics platform designed to bridge the gap between complex big data environments and actionable business outcomes. Its core architecture is built upon the n-Dimensional Behavioral Analytics (nBA) framework, which allows enterprises to process massive, disparate datasets—including transactional, social, and behavioral data—to create a holistic view of the customer. In the 2026 market landscape, Nuevora distinguishes itself by offering 'Analytics-as-a-Service' (AaaS), combining automated machine learning pipelines with human-in-the-loop expert validation. The platform excels at identifying non-obvious correlations in customer behavior, enabling precise interventions across the lifecycle, from acquisition and cross-selling to retention and advocacy. Architecturally, the platform utilizes a proprietary ensemble of algorithms that dynamically adjust to shifts in market sentiment and consumer patterns, ensuring that predictive models do not suffer from data drift. As part of Sutherland’s digital transformation suite, Nuevora provides a seamless integration layer for CRM, ERP, and marketing stacks, making it a critical asset for Fortune 500 companies seeking to operationalize AI without the overhead of building internal data science infrastructure from scratch.
n-Dimensional Behavioral Analytics that processes data across multiple behavioral vectors simultaneously.
The legal operating system built on Salesforce for high-growth firms and corporate departments.
Empowering investment and credit management with AI-driven operational alpha and cloud-native agility.
The legal industry's gold standard for AI-driven research, analytics, and Shepard’s® validated insights.
A fast, distributed, high-performance gradient boosting framework based on decision tree algorithms.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Uses a combination of Gradient Boosting, Random Forests, and Deep Learning to ensure maximum predictive accuracy.
Proprietary system that automatically identifies and creates new variables from raw data inputs.
Integrates unstructured social and text data into structured predictive models.
Continuous monitoring of model performance against real-world outcomes with automatic re-training triggers.
Sophisticated tracking of the entire customer journey to assign credit to specific touchpoints.
Predictive scoring engine capable of sub-100ms response times for real-time personalization.
Identifying at-risk customers before they defect to competitors.
Registry Updated:2/7/2026
Low conversion rates on general marketing offers for financial products.
Stagnant Average Revenue Per User (ARPU).