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Description
GoalfyData is an innovative AI data platform designed to assist teams in transforming business data and results generated by agents into reusable, governed datasets and applications. It equips AI agents with a consistent business context, which encompasses field definitions, table relationships, metric logic, processing guidelines, permissions, and usage instructions.
This eliminates the need for teams to continually upload identical files or reiterate business definitions in every AI interaction, allowing them to uphold a unified source of truth that can be utilized by various agents and collaborators. Additionally, GoalfyData enhances structured dataset management, facilitates AI-driven data analysis, ensures data governance, automates reporting, and supports the creation of dashboards and recurring data workflows.
Furthermore, AI agents are capable of querying the managed datasets, producing reports, and constructing targeted data applications while maintaining the integrity of the underlying schema, relationships, calculation rules, and access controls. The Managed Refresh feature can automate the execution of scheduled update workflows, thereby ensuring that datasets and reports remain current and relevant. In this way, GoalfyData significantly streamlines data management processes for teams.
Description
In QDeFuZZiner software, the fundamental unit is referred to as a project, which encompasses the definitions of two source datasets for import and analysis, known as the "left dataset" and "right dataset." Each project not only includes these datasets but also a variable number of solutions that detail the methodology for conducting fuzzy match analysis. Upon creation, every project is assigned a distinct project tag, which is subsequently appended to the names of the corresponding input tables during the raw data import process. This tagging system guarantees that the imported tables maintain uniqueness through association with their respective project names. Furthermore, during the import phase and later when generating and executing solutions, QDeFuZZiner establishes various indexes on the PostgreSQL database, thereby enhancing the efficiency of fuzzy data matching procedures. The datasets themselves can be sourced from spreadsheet formats such as .xlsx, .xls, .ods, or from CSV (comma separated values) flat files, which are uploaded to the server database, leading to the creation, indexing, and processing of the associated left and right database tables. This structured approach not only simplifies data management but also streamlines the analysis process, making it easier for users to derive insights from their datasets.
API Access
Has API
API Access
Has API
Screenshots View All
No images available
Integrations
PostgreSQL
Pricing Details
$12/month
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
GoalfyData
Founded
2026
Country
United States
Website
goalfydata.ai/
Vendor Details
Company Name
QDeFuZZiner
Website
zmatasoft.wixsite.com/qdefuzziner/qdefuzziner-software-features