Litify
The legal operating system built on Salesforce for high-growth firms and corporate departments.
The B2B AI engine that transforms fragmented data into predictive growth and personalized buyer journeys.
D&B Lattice (formerly Lattice Engines) is a sophisticated B2B Customer Data Platform built on the Dun & Bradstreet Data Cloud. In the 2026 landscape, it stands as a pillar of enterprise revenue operations, utilizing advanced machine learning architectures—including ensemble models and neural networks—to perform identity resolution across massive datasets. The platform's technical core is designed to ingest multi-source signals (first-party CRM data, website behavior, and global third-party intent) to create a unified view of the customer. By 2026, Lattice has matured its 'AI-First' approach, offering automated modeling that predicts not just which accounts will buy, but specifically when and what product categories they will engage with. It facilitates complex orchestration across sales and marketing silos by feeding real-time scores directly into CRM and MAP ecosystems. The infrastructure is built for high-scale enterprise environments, ensuring data compliance (GDPR/CCPA) while maintaining low-latency data syncs across global regions. As companies shift toward high-efficiency growth, Lattice’s ability to define Ideal Customer Profiles (ICP) through algorithmic precision rather than manual intuition makes it an essential tool for large-scale B2B commercial organizations.
Uses XGBoost and Random Forest algorithms to rank leads based on historical conversion patterns and real-time behavioral signals.
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.
Proprietary identity resolution algorithms that link anonymous web visitors and individual contacts to their parent corporate entities.
Combines first-party web data with third-party surge data from across the web to identify active research phases.
Automated discovery of net-new accounts that mirror the firmographic and behavioral attributes of a company’s best customers.
A low-code interface allowing non-data scientists to spin up predictive models for specific product lines.
Analyzes usage patterns, support ticket frequency, and firmographic changes to predict at-risk customers.
Real-time API calls to append hundreds of firmographic attributes to any record.
Sales teams overwhelmed by high lead volume with low conversion quality.
Registry Updated:2/7/2026
Lack of visibility into which existing customers are ready for additional products.
Wasted ad spend on accounts that aren't in-market or don't fit the ICP.