AgKnowledge

InetSoft Technology Logo
Company Size
11-200
Region
  • America
Country
  • United States
Product
  • AgKnowledge
  • InetSoft's Style Intelligence
Tech Stack
  • Cloud-based SaaS
  • AS/400 multitenant database
  • Mobile apps
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Customer Satisfaction
  • Productivity Improvements
Technology Category
  • Analytics & Modeling - Real Time Analytics
  • Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
  • Agriculture
Applicable Functions
  • Logistics & Transportation
  • Warehouse & Inventory Management
Use Cases
  • Inventory Management
  • Track & Trace of Assets
Services
  • Cloud Planning, Design & Implementation Services
  • Data Science Services
About The Customer
AgKnowledge is an industry-leading, cloud-based Agribusiness SaaS solution for medium and small fresh fruit and vegetable producers and distributors. An exciting new chapter in AgKnowledge history began in May 2018, when DiD Integration, Inc. acquired AgKnowledge Software from TechKnowledge Associates, Inc., the original developers of AgKnowledge. DiD has partnered with TechKnowledge since 2004 to bring AgKnowledge into the cloud, and since the acquisition continues to update and improve the AgKnowledge model.
The Challenge
AgKnowledge is a cloud-based SaaS solution for medium and small fresh fruit and vegetable producers and distributors. The user portal utilizes InetSoft's Style Intelligence to deliver dashboards and reports, and to provide data models which save time, as they can be reused for different clients. Data is supplied to the solution using various mobile apps, which gather both manually entered data and data collected automatically by sensors on the agricultural and shipping equipment. All client data is stored in an AS/400 multitenant database. The developers at DiD have found InetSoft’s system of logical and physical data models to be a boost of efficiency when creating dashboards for different clients. A cross-platform for all their clients linked to common data models enables the same data models to be reused and modified for various clients, each with their own specific needs.
The Solution
While some AgKnowledge clients are happy with simple reports that that allow them to filter and export raw data, AgKnowledge's more involved clients enjoy learning how to build their own agribusiness dashboards. This hands-on approach is enabled by the InetSoft data worksheet interface. Specific data needs and levels of involvement vary greatly from client to client. For example, for some reports a client will not care about data older than the past 365 days, whereas for other reports, the same client will need to see data for a several year period. Sometimes they want to see harvest data for all their facilities, and other times they want to focus a report on specific warehouses. InetSoft’s flexible data transformation interface makes it easy to accommodate each client’s individual needs and preferences.
Operational Impact
  • Data tables in the Agknowledge database often have a number of fields that can be overwhelming to less involved clients, with names that are not highly intuitive. DiD developers rectify this issue by creating data worksheets that include only the columns that the client will want to use, and then assigning descriptive column names that are easy to understand.
  • Another feature that DiD developers have used extensively is the ability to schedule reports or tasks, have them run autonomously, and export the results via email. This automation is a big time saver for AgKnowledge clients who rely on regular reports to track their production in real time.
  • Some clients have schedules that run overnight, using InetSoft’s proprietary data grid cache to build a cache of relevant data for reports and dashboards that run on the following day.
  • Clients also enjoy the ability to bookmark a report or dashboard so that when they open it every day they see what they've saved the day before, and make their desired changes. This eliminates the need to remember and re-apply specific filters that the client uses regularly.

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