Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Utilize natural language processing to derive insights from unstructured text without needing machine learning expertise, leveraging a suite of features from Cognitive Service for Language. Enhance your comprehension of customer sentiments through sentiment analysis and pinpoint significant phrases and entities, including individuals, locations, and organizations, to identify prevalent themes and trends. Categorize medical terminology with specialized, pretrained models tailored for specific domains. Assess text in numerous languages and uncover vital concepts within the content, such as key phrases and named entities encompassing people, events, and organizations. Investigate customer feedback regarding your brand while analyzing sentiments related to particular subjects through opinion mining. Moreover, extract valuable insights from unstructured clinical documents like doctors' notes, electronic health records, and patient intake forms by employing text analytics designed for healthcare applications, ultimately improving patient care and decision-making processes.
Description
Docxonomy offers businesses an advanced insight platform that enables the exploration and examination of both unstructured and structured data secured within their networks, irrespective of its storage location. Utilizing cutting-edge artificial intelligence and machine learning technologies, Docxonomy can process a wide array of file formats, such as Office documents, PDFs, videos, audio files, and images. By extracting context and significance from this data, including specific industry jargon, the platform efficiently categorizes files, detects entities, identifies similarities, and provides answers to inquiries. Furthermore, organizations can implement Docxonomy either on-premises or on their preferred cloud services, eliminating the need for extensive consulting engagements. The setup process is remarkably swift, typically taking only hours or days rather than the weeks or months commonly associated with traditional solutions. Tailored for specific industries, our platform allows immediate access to valuable insights, empowering users to enhance their drug delivery processes without the burden of costly migrations or extensive projects. In this way, Docxonomy not only promotes efficiency but also fosters a data-driven culture within enterprises.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Adobe Acrobat
No
Azure Marketplace
Yes
TAS Insight Engine
Yes
Unremot
Yes
Integrations
Adobe Acrobat
Yes
Azure Marketplace
No
TAS Insight Engine
No
Unremot
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
azure.microsoft.com/en-us/services/cognitive-services/text-analytics/
Vendor Details
Company Name
Docxonomy
Founded
2017
Country
United States
Website
docxonomy.com
Product Features
Natural Language Processing
Co-Reference Resolution
Yes
In-Database Text Analytics
Yes
Named Entity Recognition
Yes
Natural Language Generation (NLG)
Yes
Open Source Integrations
Yes
Parsing
No
Part-of-Speech Tagging
Yes
Sentence Segmentation
Yes
Stemming/Lemmatization
Yes
Tokenization
No
Product Features
Enterprise Search
AI / Machine Learning
No
Faceted Search / Filtering
No
Full Text Search
No
Fuzzy Search
No
Indexing
No
Text Analytics
No
eDiscovery
No