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Features

High-Performing and Ready-to-Use NLP Solutions

Jumpstart your text processing with Lettria's NLP modules. Trained meticulously on our proprietary datasets, they deliver 30% better performance* on average over open-source solutions, while ensuring full transparency and accessibility from Day 1.

Amplify Insights with Sentiment Analysis

Leverage Lettria's Deep Learning-powered Sentiment Analysis, that is 30% more accurate* than a comparable open source model.

Our advanced solution deciphers and quantifies sentiment from -1 to 1 and detects different sentiments in different parts of the same sentence, allowing you to propel informed decisions, optimize brand reputation, and enhance customer experience with actionable insights.

Unleash Advanced Emotion Analysis

Empower your business with Lettria's deep learning-powered Emotion Analysis, capable of detecting up to 28 distinct emotions in text. A game-changer for elevating customer satisfaction, gauging public sentiment, and enriching user experiences.

Understand meaning with Entity Recognition

Lettria's Entity Recognition capabilities go way beyond standard open-source NER tools. In the same text, you can recognize regular entities, numeric entities, as well as meanings.

Identify a cappuccino as a "hot beverage" or a MacBook as an "electronic device", while extracting email IDs, phone numbers and scientific measurements from your text. The possibilities are endless.

The key to any successful data science project is the data collection phase.

Patrick Duvaut

Head of Innovation

The key to any successful data science project is the data collection phase.

Patrick Duvaut

Head of Innovation

The key to any successful data science project is the data collection phase.

Patrick Duvaut

Head of Innovation

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*30% more accurate when comparing F1 scores of the best HuggingFace model and Lettria’s model, on a dataset of 20,000 customer reviews generated by GPT. Lettria’s model attained a 94% F1 score, which is a 30% increase over the best HuggingFace model, which attained 75%.