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Cloud-Nanny Technographics
Discover the latest software purchases and digital transformation initiatives being undertaken by Cloud-Nanny and its business and technology executives. Each quarter our research team identifies on-prem and cloud applications that are being used by the 6 Cloud-Nanny employees from the public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources.
During our research, we have identified that Cloud-Nanny has purchased the following applications: IBM Analytics for Apache Spark (Managed Cloud Spark Service) for ML and Data Science Platforms in 2016 and the related IT decision-makers and key stakeholders.
Our database provides customer insight and contextual information on which enterprise applications and software systems Cloud-Nanny is running and its propensity to invest more and deepen its relationship with IBM 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 Cloud-Nanny 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 Cloud-Nanny 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.
AI Development
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| IBM | Legacy | IBM Analytics for Apache Spark (Managed Cloud Spark Service) | ML and Data Science Platforms | AI Development | n/a | 2016 | 2017 |
In 2016, Cloud-Nanny deployed IBM Analytics for Apache Spark (Managed Cloud Spark Service) as the core of its ML and Data Science Platforms implementation for real time website classification and decisioning. The project targeted sub 40 microsecond lookups to decide whether to allow or block hundreds of thousands of web requests, emphasizing ultra low latency inference in a consumer facing parental control service.
Cloud-Nanny used IBM Analytics for Apache Spark (Managed Cloud Spark Service) to train and maintain a website classifier on a managed Spark cluster, producing categorical labels such as gaming, video, and adult content. The classifier is applied when a site is not already present in the curated database, and the inference output is compared against per family profiles to determine allow or block, or to escalate to a parental decision.
The implementation combined IBM dashDB as a managed cloud database for rapid blacklist and whitelist lookups with the managed Spark service for model training and online classification, all provisioned on IBM Bluemix to accelerate development and operations. Lookup latency and inference orchestration were engineered to minimize impact on the end user browsing experience, and parental decisions captured during escalations are fed back into the model training pipeline to support continuous learning.
Cloud-Nanny took the solution from proof of concept to production in 14 months, noting that building on Bluemix materially accelerated time to market, an estimated 50 percent faster than the company experienced with previous infrastructure setup. Operational governance centers on per family policy profiles and an interactive escalation workflow for human review, while iterative model retraining on the managed Spark cluster enables the classifier to adapt over time.
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