Bangkok, 10400,
Thailand
Forth Smart Corporation Technographics
Discover the latest software purchases and digital transformation initiatives being undertaken by Forth Smart Corporation and its business and technology executives. Each quarter our research team identifies on-prem and cloud applications that are being used by the 1540 Forth Smart Corporation employees from the public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources.
During our research, we have identified that Forth Smart Corporation has purchased the following applications: Oracle Analytics Cloud for Analytics and BI in 2021, Oracle Autonomous Database for Database Management in 2021, Oracle DataScience.com Platform for ML and Data Science Platforms in 2021 and the related IT decision-makers and key stakeholders.
Our database provides customer insight and contextual information on which enterprise applications and software systems Forth Smart Corporation is running and its propensity to invest more and deepen its relationship with Oracle or identify new suppliers as part of their overall Digital and IT transformation projects to stay competitive, fend off threats from disruptive forces, or comply with internal mandates to improve overall enterprise efficiency.
We have been analyzing Forth Smart Corporation revenues, which have grown to $265.0 million in 2024, plus its IT budget and roadmap, cloud software purchases, aggregating massive amounts of data points that form the basis of our forecast assumptions for Forth Smart Corporation intention to invest in emerging technologies such as AI, Machine Learning, IoT, Blockchain, Autonomous Database or in cloud-based ERP, HCM, CRM, EPM, Procurement or Treasury applications.
Analytics and BI
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| Oracle | Legacy | Oracle Analytics Cloud | Analytics and BI | Analytics and BI | n/a | 2021 | 2022 |
|
IaaS
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| Oracle | Legacy | Oracle Autonomous Database | Database Management | IaaS | n/a | 2021 | 2022 |
|
AI Development
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| Oracle | Legacy | Oracle DataScience.com Platform | ML and Data Science Platforms | AI Development | n/a | 2021 | 2022 |
In 2021, Forth Smart Corporation deployed Oracle DataScience.com Platform as part of its ML and Data Science Platforms stack to operationalize analytics for a nationwide kiosk network. The implementation targeted business functions in marketing, analytics, and operations to support a lean staff of 300 employees operating more than 120,000 kiosks that serve 15 million users and process over 2 million transactions per day. Forth Smart Corporation Oracle DataScience.com Platform is positioned to provide data science tooling and model lifecycle capabilities aligned with the scale and cadence of kiosk transaction streams.
The implementation emphasized core data science capabilities including model training and experimentation, notebook based analytics, and model deployment workflows common to ML and Data Science Platforms. Teams used the Oracle DataScience.com Platform to build predictive customer segmentation and offer propensity models, and to run automated model scoring as part of campaign orchestration. Oracle Machine Learning algorithms were applied through the platform to convert analytical output into operational scoring and offer recommendations for kiosk screens and ewallet top up flows.
Architecturally the Oracle DataScience.com Platform was integrated with Oracle Autonomous Database and Oracle Autonomous Data Warehouse running on Oracle Cloud Infrastructure, with Oracle Analytics feeding visualization and ad effectiveness analysis back into the data science pipeline. The platform consumed kiosk transaction streams and consolidated historical records for feature engineering, then wrote model outputs and scored datasets back into the Autonomous Data Warehouse for downstream reporting and activation. This integration pattern supported secure data handling and near real time insight generation across the kiosk footprint.
Governance and operational change centered on empowering business analysts to own experimentation and model iteration without a dedicated database administrator, while preserving centralized data security controls. Analysts reported shortening query times from three hours to minutes, and business stakeholders cited a doubling to threefold increase in ad conversion rates as a result of predictive targeting and analytics driven offer testing. The deployment reflects a production oriented ML and Data Science Platforms implementation focused on operational scoring, campaign optimization, and secure, automated data workflows.
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