Average Ratings 28 Ratings
Average Ratings 0 Ratings
Description
Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence.
Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs.
Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500 companies, such as United, Kroger, Philips, Truist, and many others.
Description
The rapid expansion of consumer data over the last ten years is now being eclipsed by a remarkable surge in business data, creating both unique opportunities and significant challenges for companies and cloud service providers alike. This situation necessitates a revolutionary approach to developing and scaling storage infrastructure. Our vision for this evolution is embodied in the Infinidat Elastic Data Fabric, which reimagines enterprise storage, transitioning from conventional hardware appliances to flexible, high-performance pools of digital storage that are both highly reliable and cost-effective, with effortless data mobility across data centers and public cloud environments. Today, professionals in various industries are grappling with a similar challenge due to the wave of digital transformation influencing their operations. As traditional hardware-based storage solutions are becoming prohibitively expensive and increasingly difficult to manage, they also fall drastically short of the requirements for the data-centric future. Consequently, it is imperative for these systems to transform into innovative software-defined on-premises enterprise storage clouds to meet the demands of the evolving digital landscape. This shift not only enhances efficiency but also positions organizations to better harness the power of their data.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Axis LMS
Confluence
Databricks
Facebook
Facebook Ads
GitHub
GitLab
Gmail
Google Cloud Platform
Integrations
Amazon Web Services (AWS)
Axis LMS
Confluence
Databricks
Facebook
Facebook Ads
GitHub
GitLab
Gmail
Google Cloud Platform
Pricing Details
$0.25/credit
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Gathr.ai
Country
United States
Website
www.gathr.ai
Vendor Details
Company Name
Infinidat
Founded
2011
Country
Israel
Website
www.infinidat.com/sites/default/files/resource-pdfs/Infinidat%20Elastic%20Data%20Fabric%20White%20Paper.pdf
Product Features
Data Fabric
Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Streaming Analytics
Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards
Product Features
Data Fabric
Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management