The world's most powerful NLP engine for transforming unstructured text into structured, high-fidelity business intelligence.
Lexalytics, an InMoment company, serves as the gold standard for text analytics and Natural Language Processing (NLP) in 2026. Its core technology, the Salience engine, is engineered for massive horizontal scalability, processing billions of documents daily across hundreds of languages. Unlike surface-level sentiment tools, Lexalytics utilizes a multi-layered technical architecture that combines deep learning models with advanced linguistic rules to achieve unmatched precision in sentiment scoring, theme extraction, and named entity recognition. Its 2026 market positioning focuses on the 'Intelligence of Things,' integrating seamlessly with Generative AI workflows to provide the underlying structured data needed for RAG (Retrieval-Augmented Generation) systems. The platform offers two primary deployment modes: the Semantria SaaS API for cloud-native agility and the Salience SDK for high-performance, on-premise, or edge computing requirements. By providing granular control over syntax-based sentiment and custom entity dictionaries, Lexalytics enables global enterprises to extract nuanced insights from complex datasets, including financial filings, social media streams, and internal support tickets, ensuring that data-driven decisions are based on accurate, context-aware analysis.
A high-performance C++ engine that performs tokenization, part-of-speech tagging, and dependency parsing at the millisecond level.
The industry-standard Python library for high-performance Chinese text segmentation and keyword extraction.
The industry standard for memory-efficient topic modeling and semantic document similarity.
Transform unstructured language into actionable intelligence using hybrid AI technology.
No-code text analysis and data visualization for automated customer experience intelligence.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Analyzes the grammatical structure of a sentence to link specific adjectives to specific subjects.
Extracts people, places, things, and custom entities using a hybrid of regex and machine learning.
Classifies text based on the likelihood of the speaker's intent: Buy, Sell, Complain, or Recommend.
Unsupervised learning algorithm that identifies emerging topics across a dataset without pre-defined tags.
Uses word embeddings to determine the relationship between disparate terms in a specific context.
The ability to run the exact same NLP models in the Semantria cloud or locally via the Salience SDK.
Monitoring massive amounts of clinical trial data and social medical forums for adverse event reporting.
Registry Updated:2/7/2026
Hedge funds needing to quantify the mood of earning calls and news wires faster than competitors.
Large retailers failing to consolidate feedback from surveys, social, and chat.