The Ultimate Text & Identity Analytics Suite

Accurate, Scalable, and Trusted AI and Machine Learning-powered products for entity extraction, fuzzy name matching, and more

Text Analytics

Derive deep insights from text using AI

Identity Analytics

Match names intelligently with Machine Learning

Entity Extraction

NetOwl’s highly accurate entity extraction identifies over 100 types of named entities in unstructured text at scale and in multiple languages. Designed for Big Data, it delivers extremely fast performance with simple integration into your existing analytics pipelines.

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Name Matching

NetOwl’s award-winning, machine learning-based fuzzy name matching provides fast and accurate cross-lingual matching. It is proven in mission-critical environments such as anti-money laundering (AML), regulatory compliance (KYC/PEP), border security, and counterterrorism.

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Event Extraction

NetOwl’s event extraction is innovative advanced text analytics technology that identifies over 100 event types and their event participants in domains such as business, politics, and law. It is a key technology for Adverse Media Monitoring, Intelligence Analysis, and Link Analysis among others.

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Identity Resolution

Resolve identities quickly and accurately across large datasets in high-volume environments. NetOwl’s intelligent identity resolution works by combining evidence across multiple attributes, including names, date of birth, nationality, addresses, phone numbers, and employers.

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Deploy on Premise or in the Cloud

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#1

in MITRE Name Matching Challenge

Top

choice for AI-based Analytics

Best

in international benchmarking events

20+

years of experience

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How is NetOwl Used?

Sample Solutions

Text Analytics

Intelligence Analysis

Intelligence analysts must analyze staggering amounts of data from multiple sources in multiple languages to identify critical information and discover hidden links. NetOwl text analytics software turns unstructured data into structured information that can be easily searched, visualized, and exploited by other analytical tools. NetOwl’s advanced entity extraction supports semantic search and link analysis while geotagging enables geospatial analysis of text.

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Different denominations of money from multiple countries

Identity Analytics

AML, KYC, PEP

Financial firms across the world must ensure that they are compliant with applicable laws and regulations focused on the prevention of money laundering (AML) and terrorist financing (KYC, PEP). NetOwl’s identity analytics, powered by AI and machine learning, helps financial organizations reduce compliance risk through its high-recall high-precision fuzzy name matching while supporting consistent, repeatable compliance processes.

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Text Analytics

Adverse Media Monitoring

Monitoring massive volumes of news and other sources for a timeline awareness of adverse information about individuals or companies of interest is critical for AML, KYC, and due diligence. NetOwl’s advanced entity, relationship, and event extraction allows its customers to detect potential risks earlier (e.g., bankruptcies, lawsuits, indictments, arrests, corruption) and respond quickly by analyzing large volumes of text and identifying adverse information at scale and in real time.

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Identity Analytics

Border Security

Robust border security requires accurate and fast matching of names against a variety of watch lists. Watch lists often contain names from different ethnicities and cultural backgrounds, which pose a variety of matching challenges, including transliteration variants, name order variations, orthographic differences, etc. NetOwl’s award-winning, machine learning-based approach provides highly accurate, fast, and scalable intelligent name matching.

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