NaturalText is an AI-powered data analysis platform that enables organisations to gain deep insights from structured and unstructured text data, as well as private papers. It uses unsupervised learning and symbolic AI to produce outcomes that are completely intelligible and free of bias.
It does not require any prior training or cloud uploads, making it suitable for handling sensitive or confidential data. This data analysis application uses intelligent grouping, content/context awareness, and logical reasoning to determine what your data is really saying.
NaturalText Deal Features Overview:
Whether you’re a research institution, a nonprofit, or a huge corporation dealing with complex, multilingual datasets, the tool makes data extraction and analysis secure and local
Clustering, rating, and other distinct NLP features enable the extraction of insights deep within natural language text sources
Goes beyond analysing only the language to comprehend the substance and context of the texts
Allows for infinite data analysis
Allows for the simultaneous examination of up to 5000 rows/sentences
Works completely automatically with no pre-training
Allows you to discover hidden patterns and important insights in structured/unstructured data and private papers
Utilises substantial data science and NLP (Natural Language Processing) skills to assess your organisation’s needs and create a tailored plan
Works similarly for both low-volume data from small organisations and high-volume data from large organisations
Provides a thorough awareness of customer and market trends.
Data is extracted from social media, reviews, and other sources to provide insights
Analyses user queries and other data to enhance recommendation systems, search relevancy, and business efficiency
Analyses data and documents in 5 minutes, saving both time and money
Installs locally on Linux, Windows, or Mac
There is no need to shift data to the cloud, install new cybersecurity procedures, or be concerned about the prospect of a data breach
It produces human-readable, explainable, and intelligible outcomes, making it easier to streamline procedures
Uses logical thinking rather than statistical facts to produce relevant, informative, and actionable outcomes
Its algorithms are based on graph theory and other non-statistical mathematical theories
Text is treated as symbols in order to identify patterns and address language comprehension challenges.
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