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What is KITRO?

KITRO presents a cutting-edge automated solution specifically designed for the management of food waste in the food and beverage industry. Utilizing sophisticated artificial intelligence, the KITRO system seamlessly integrates with existing kitchen operations, allowing for the monitoring and evaluation of food waste without imposing additional tasks on staff. This innovative solution functions by taking photographs of discarded items, precisely identifying and quantifying them, and offering detailed insights through a tailored dashboard. Armed with this data, businesses can set objectives, implement targeted strategies, and potentially decrease food waste by up to 30% in just six months, resulting in significant cost savings and a positive impact on the environment. The versatility of KITRO's solutions enables their application in diverse food service settings, including hotels, canteens, restaurants, and healthcare facilities, while ensuring easy installation and an intuitive user experience. Committed to fostering long-term sustainability, the company provides continuous support to its clients, guiding them toward maximizing their waste reduction initiatives. Additionally, KITRO's strategy not only streamlines waste management processes but also cultivates a culture of environmental stewardship across the food service sector. This holistic approach reinforces the importance of sustainability and encourages industry-wide participation in responsible waste practices.

What is Auger.AI?

Auger.AI offers a robust solution aimed at ensuring the accuracy of machine learning models. Our Machine Learning Review and Monitoring (MLRAM) tool plays a crucial role in keeping your models' precision consistent over time. It also evaluates the return on investment for your predictive analytics efforts! MLRAM's compatibility with any machine learning technology stack enhances its flexibility and adaptability. Failing to regularly assess the accuracy of your machine learning system lifecycle could lead to financial losses due to inaccurate predictions. Additionally, the ongoing requirement for model retraining can be expensive and may not resolve issues related to concept drift. MLRAM provides substantial advantages for both data scientists and business stakeholders, including features such as accuracy visualization graphs, performance alerts, anomaly detection, and automated optimized retraining. The process of integrating your predictive model with MLRAM is incredibly straightforward, requiring just a single line of code. We also offer a free one-month trial of MLRAM for qualifying users. With Auger.AI, you can leverage the most reliable AutoML platform available, empowering your organization to enhance its predictive capabilities to the fullest. This comprehensive approach ensures that your machine learning initiatives remain efficient and cost-effective over time.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Google Cloud Platform
Microsoft Azure
TensorFlow

Integrations Supported

Amazon Web Services (AWS)
Google Cloud Platform
Microsoft Azure
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$200 per month
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

KITRO

Date Founded

2017

Company Location

Switzerland

Company Website

www.kitro.ch/

Company Facts

Organization Name

Auger.AI

Date Founded

2019

Company Location

United States

Company Website

auger.ai/

Categories and Features

Categories and Features

Deep Learning

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

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