Abdulrahman Khalaf Al Sharida For Pots Technographics
Discover the latest software purchases and digital transformation initiatives being undertaken by Abdulrahman Khalaf Al Sharida For Pots and its business and technology executives. Each quarter our research team identifies on-prem and cloud applications that are being used by the 10 Abdulrahman Khalaf Al Sharida For Pots employees from the public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources.
During our research, we have identified that Abdulrahman Khalaf Al Sharida For Pots has purchased the following applications: Amazon Pay for Payment Processing in 2022, Sift Science Digital Trust Platform for ML and Data Science Platforms in 2022, Shopify for eCommerce 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 Abdulrahman Khalaf Al Sharida For Pots is running and its propensity to invest more and deepen its relationship with Amazon Web Services (AWS) , Apple , Sift Science 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 Abdulrahman Khalaf Al Sharida For Pots revenues, which have grown to $1.0 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 Abdulrahman Khalaf Al Sharida For Pots 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.
ERP Financial Management
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
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| Amazon Web Services (AWS) | Legacy | Amazon Pay | Payment Processing | ERP Financial Management | n/a | 2022 | 2022 |
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Payment Processing | ERP Financial Management |
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2022 | 2022 |
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AI Development
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| Sift Science | Legacy | Sift Science Digital Trust Platform | ML and Data Science Platforms | AI Development | n/a | 2022 | 2022 |
In 2022, Abdulrahman Khalaf Al Sharida For Pots deployed Sift Science Digital Trust Platform on its website. The implementation uses the Sift Science Digital Trust Platform within the ML and Data Science Platforms category to instrument customer facing sessions and enable automated risk scoring for online interactions.
Deployment focused on client side web instrumentation to capture device signals and behavioral data, with event feeds feeding Sift models for real time risk assessment. Functional capabilities implemented include behavioral analytics, automated trust scoring and decisioning, device intelligence and session risk assessment, reflecting standard digital trust and fraud detection workflows. Configuration work emphasized event enrichment and real time scoring rules to support automated decisions during account creation and checkout flows.
Operational scope is limited to the company website and customer facing online channels in Saudi Arabia, aligned to the companys distribution business and 10 employee footprint. Business functions impacted include online operations, customer service and order review processes through use of Sift Science Digital Trust Platform risk signals. Integration points are confined to website instrumentation and internal event routing, with risk signals feeding manual review queues and automated flagging logic.
Governance was adjusted for centralized oversight by the online operations function, with thresholds and escalation paths configured inside the Sift Science Digital Trust Platform to drive consistent trust decisions and reviewer workflows. The narrative reflects a small scale, site centric rollout that leverages ML driven scoring to surface high risk sessions for manual handling.
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CRM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
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Customer Experience | CRM |
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2022 | 2022 |
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Digital Advertising Platform | CRM |
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2022 | 2022 |
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Marketing Analytics | CRM |
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2022 | 2022 |
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Tag Management | CRM |
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2022 | 2022 |
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IaaS
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
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Content Delivery Network | IaaS |
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2022 | 2022 |
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