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features
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support

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Description

FeedStock employs advanced multilingual deep learning technology to capture, recognize, and extract crucial information from your communication channels, transforming it into valuable actionable insights. The complexity of B2B buying has significantly evolved, as evidenced by the increase in necessary contacts for making purchasing decisions, which rose from 17 in 2019 to 27 by 2021. With fewer face-to-face interactions and increasing challenges in outbound growth, our fully automated intelligent assistance is designed to enhance revenue generation for relationship-focused sales teams. By analyzing client interactions directly from your inbox, we unlock hidden growth potential through previously unnoticed insights. You can expect immediate value without the burden of expensive, lengthy adoption processes; when you activate FeedStock, it is fully operational. We capture and categorize ten times more relationships, extract millions of topics, and provide unmatched proprietary insights that drive your business growth, ensuring you stay ahead in a rapidly changing market landscape. This streamlined approach empowers your teams to focus on what really matters: building stronger connections and driving sales.

Description

Enhance the efficiency of your deep learning projects and reduce the time it takes to realize value through AI model training and inference. As technology continues to improve in areas like computation, algorithms, and data accessibility, more businesses are embracing deep learning to derive and expand insights in fields such as speech recognition, natural language processing, and image classification. This powerful technology is capable of analyzing text, images, audio, and video on a large scale, allowing for the generation of patterns used in recommendation systems, sentiment analysis, financial risk assessments, and anomaly detection. The significant computational resources needed to handle neural networks stem from their complexity, including multiple layers and substantial training data requirements. Additionally, organizations face challenges in demonstrating the effectiveness of deep learning initiatives that are executed in isolation, which can hinder broader adoption and integration. The shift towards more collaborative approaches may help mitigate these issues and enhance the overall impact of deep learning strategies within companies.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AUSIS No 
IBM Intelligent Video Analytics No 

Integrations

AUSIS Yes 
IBM Intelligent Video Analytics Yes 

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 Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

FeedStock

Founded

2015

Country

United Kingdom

Website

feedstock.com/products/synapse/

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/deep-learning-platform

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 

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 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training Yes 
Natural Language Processing (NLP) No 
Predictive Modeling Yes 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

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