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What is Pienso?

Creating a topic model from scratch demands advanced programming expertise, which can be both costly and may overshadow the critical comprehension of the underlying data. This technical knowledge often detracts from the fundamental insights that data can provide. The manual process of labeling training data is not only painstaking and labor-intensive but also incurs significant costs. While outsourcing this labeling task to lower-wage workers may speed up the process and lower expenses, it frequently compromises the quality and detail of the results. Each of these approaches leads to a static classification system that can be difficult to modify over time. It is essential to move beyond simple tagging and empower subject matter experts to actively engage with their data to facilitate modeling and analysis. With an abundance of text data available, rich with insights waiting to be uncovered, the necessity for robust tools becomes increasingly evident. Pienso offers a solution to this problem by allowing you to train models using your own data, acknowledging that this personalized method produces the most effective outcomes. Regardless of the nature of your data, whether it is unstructured, semi-structured, lengthy, or concise, Pienso is designed to help you convert it into actionable insights that can inform strategic decision-making. By utilizing Pienso, you have the opportunity to fully harness the capabilities of your data while avoiding the conventional challenges commonly associated with topic modeling. This innovative approach not only simplifies the process but also enhances the overall quality of insights derived from your data.

What is Cauliflower?

Cauliflower is capable of processing feedback and comments related to all kinds of services or products. Utilizing Artificial Intelligence (AI), Cauliflower identifies key topics, assesses their significance, and establishes connections between them. It employs proprietary machine learning models designed to extract relevant content and gauge sentiment accurately. The platform features user-friendly dashboards equipped with filtering options and the ability to drill down into specific data points. Users can utilize various parameters to specify language, weight, ID, and timeframes. Additionally, custom filter variables can be defined from a dropdown menu. If needed, Cauliflower can translate its findings into a standardized language to ensure consistency. By adopting a company-wide language, businesses can move beyond sporadic readings of customer feedback and avoid simply quoting isolated opinions, thus fostering a more cohesive understanding of customer sentiment. This approach ultimately enhances strategic decision-making and improves overall customer engagement.

Media

Media

Integrations Supported

Amazon
Google Business Profile
Google Play
Tripadvisor
Trustpilot
Yelp

Integrations Supported

Amazon
Google Business Profile
Google Play
Tripadvisor
Trustpilot
Yelp

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Pienso

Date Founded

2016

Company Location

United States

Company Website

www.pienso.com

Company Facts

Organization Name

Cauliflower

Date Founded

2019

Company Location

Germany

Company Website

www.cauliflower.ai/

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Text Mining

Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering

Categories and Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Customer Experience

Action Management
Analytics
Customer Segmentation
Dashboard
Feedback Management
Knowledge Management
Multi-Channel Collection
Sentiment Analysis
Survey Management
Text Analysis
Trend Analysis

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Qualitative Data Analysis

Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis

Text Mining

Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering

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