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Text analysis

NetOwl ✓

AI-powered text and identity analytics for Big Data.

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Text Analytics Big Data Identity Analytics
More categories (4)
Entity Extraction Event Extraction Identity Resolution Text analysis
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Verdict

A quick read before you dig into the full page.

Best if
AI-powered text and identity analytics for Big Data
Skip if
Complex deployment options
Pick this when
Comprehensive text analytics

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Overview

NetOwl is a comprehensive suite of AI-based tools designed for text analytics and identity analytics within Big Data contexts. Its Text Analytics tools comprise entity, relationship, and event extraction; sentiment analysis; geotagging; and categorization.

This allows users to derive deep insights from unstructured data by identifying and extracting key elements and sentiments from textual information. Furthermore, its Identity Analytics tools provide name matching and identity resolution.

These use machine learning to match names quickly and accurately in various languages. NetOwl also provides specific applications such as anti-money laundering (AML), regulatory compliance (KYC, PEP), border security, and counterterrorism thanks to its accurate and scalable matching technology.

Additionally, NetOwl caters to diverse domains, extending its functionality to enterprise search, e-discovery, adverse media monitoring, social media analysis, and intelligence analysis.

For versatility, the tool suite can be deployed either on-premise or in the cloud. Its proprietary technology makes it an effective asset for organizations dealing with vast volumes of data, requiring intelligent extraction of insights, and helping to not only detect but prevent potential threats.

NetOwl website

Access & connections

Where you can use NetOwl.

Platforms

Web

Capabilities

What this tool accepts, produces, and is strongest at.

Input

  • Text

Output

  • Text
  • Geo
  • Tabular

Pros & cons

Pros

  • Comprehensive text analytics
  • Identity analytics included
  • Big Data compatible
  • Entity, relationship, event extraction
  • Sentiment analysis feature
  • Geotagging capabilities
  • Categorization tool
  • Name matching tool
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  • Identity resolution tool
  • Multilingual functionality
  • Anti-money laundering application
  • Regulatory compliance application
  • Border security application
  • Counterterrorism application
  • Enterprise search capable
  • E-discovery function
  • Adverse media monitoring
  • Social media analysis
  • Intelligence analysis
  • On-premise or cloud deployment
  • Scalable matching technology
  • Versatile in diverse domains
  • Accurate extraction of insights
  • Threat detection and prevention
  • High accuracy of tools
  • Supports semantic search
  • Employs link analysis
  • Enables geospatial analysis
  • Specialized applications available

Cons

  • Complex deployment options
  • May overwhelm inexperienced users
  • Requires high data volumes
  • Limited to text analytics
  • Specific domain extension needed
  • Proprietary technology lock-in
  • Multilingual support unclear
  • No clear API mentioned
Show 2 more
  • Potential high cost
  • Limited use case versatility

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Releases 1

Initial release January 19, 2022 Current
Initial release of NetOwl.

FAQ 12

What is NetOwl?
NetOwl is a comprehensive suite of AI-based tools designed for text analytics and identity analytics within Big Data contexts.
What are the main features of NetOwl?
The main features of NetOwl include entity, relationship, and event extraction; sentiment analysis; geotagging; categorization; name matching; and identity resolution. It also provides specific applications like anti-money laundering, regulatory compliance, border security, and counterterrorism due to its accurate and scalable matching technology.
Can NetOwl analyze data in multiple languages?
Yes, NetOwl has the ability to analyze data in multiple languages.
Does NetOwl have name matching capabilities?
Yes, NetOwl has name matching capabilities. Its Identity Analytics tools provide name matching, using machine learning to match names quickly and accurately.
Does NetOwl offer text and identity analytics?
Yes, NetOwl offers both text and identity analytics. The text analytics tools allow users to derive deep insights from unstructured data while the identity analytics tools offer name matching and identity resolution.
How can NetOwl assist with regulatory compliance such as AML, KYC, and PEP?
NetOwl can assist with regulatory compliance such as AML, KYC, and PEP by offering precise and scalable name matching and identity resolution services. It verifies that customers are not on any sanctions lists, ensuring they are not involved in money laundering or terrorist financing.
How can NetOwl enhance border security and counterterrorism efforts?
NetOwl enhances border security and counterterrorism efforts by providing robust and accurate name matching against watch lists. Its technology can handle variations in transliteration, name order, and orthography across different cultures and languages.
Can NetOwl be used for social media analysis?
Yes, NetOwl can be used for social media analysis. It effectively analyzes unstructured data, providing deep insights.
Is NetOwl useful in the field of enterprise search and e-discovery?
Yes, NetOwl proves useful in the field of enterprise search and e-discovery by delivering advanced text analytics that can extract relevant information from large volumes of unstructured data.
Can NetOwl be deployed both on-premise and in the cloud?
Yes, NetOwl offers versatility in deployment. It can be deployed both on-premise and in the cloud.
How does NetOwl perform sentiment analysis?
NetOwl performs sentiment analysis by not just recognizing simple positive vs. negative sentiments, but also offering entity-based sentiment analysis. It captures what exactly people like or do not like and provides deep insights into their opinions, attitudes, intentions, and behaviors.
What capabilities does NetOwl offer for entity, relationship, and event extraction?
NetOwl's entity, relationship, and event extraction features allow for a broad semantic ontology and not only extract named entities but also links and events with high accuracy, making it ideal for Big Data Analysis of unstructured data.
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