Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Our advanced natural language processing technology harnesses the power of AI to capture, analyze, and visualize insights from all forms of customer communication. This includes call transcriptions, chat conversations, emails, support tickets, return claims, social media interactions, and surveys, all supported in 47 languages. With Explorer, users can quickly analyze open-ended text responses in just a few minutes. Additionally, Explorer features an API that enables seamless integration of unstructured text data into your business intelligence systems. The field of employee experience focuses on analyzing and identifying the elements that contribute to employee satisfaction and motivation. Our offerings empower businesses to efficiently process, analyze, and derive meaning from vast amounts of unstructured natural language data in a fraction of the usual time. The platform is designed to be user-friendly, allowing you to create custom bots tailored to your specific business requirements without any coding knowledge necessary. You can achieve immediate efficiency improvements within just minutes of setup. Moreover, the Gavagai API provides a suite of semantic analysis tools that support 47 languages, allowing for immediate access to user-friendly endpoints. This robust capability ensures that organizations can effectively leverage insights from their data to enhance decision-making processes.
Description
Developing a topic model from the ground up requires a high level of programming skill. This specialized knowledge can be costly and often overshadows the essential understanding of the data itself. The process of manually labeling your training data is not only time-consuming but also labor-intensive and expensive. Outsourcing this task to low-wage workers may expedite the process and reduce costs, yet it often sacrifices both accuracy and detail. Each of these methods results in a static taxonomy that can be challenging to adapt over time. It's crucial to transition away from mere tagging and empower subject matter experts to engage with their data for modeling and analysis. With vast amounts of text data at your disposal, brimming with insights ready for exploration, the need for effective tools becomes clear. Pienso is here to assist with this challenge by enabling you to train models using your own data, as we recognize that this approach yields the best results. Regardless of whether your data is unstructured, semi-structured, lengthy, or concise, Pienso is equipped to help you transform it into valuable insights that can drive decision-making. By leveraging Pienso, you can unlock the full potential of your data without the traditional hurdles associated with topic modeling.
API Access
Has API
Yes
API Access
Has API
No
Integrations
SurveyMonkey Enterprise
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Gavagai
Founded
2009
Country
Sweden
Website
www.gavagai.io
Vendor Details
Company Name
Pienso
Founded
2016
Country
United States
Website
www.pienso.com
Product Features
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No
Text Mining
Boolean Queries
No
Document Filtering
No
Graphical Data Presentation
No
Language Detection
No
Predictive Modeling
No
Sentiment Analysis
No
Summarization
No
Tagging
No
Taxonomy Classification
No
Text Analysis
No
Topic Clustering
No
Product Features
Deep Learning
Convolutional Neural Networks
No
Document Classification
No
Image Segmentation
No
ML Algorithm Library
No
Model Training
No
Neural Network Modeling
No
Self-Learning
No
Visualization
No
Text Mining
Boolean Queries
No
Document Filtering
No
Graphical Data Presentation
No
Language Detection
No
Predictive Modeling
No
Sentiment Analysis
No
Summarization
No
Tagging
No
Taxonomy Classification
No
Text Analysis
No
Topic Clustering
No