ZaaS (Class 42)
#5542378
Application Number:5542378
Status:
Unknown
Class:42
Applicant: ZASTI INDIA PRIVATE LIMITED
Filing Date:Sun, 24 Jul 2022
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Trademark Information
| Trademark | ZaaS |
| Trademark Type | Wordmark |
| Class | 42 |
| Application Number | 5542378 |
| Nature/Scope of business | Design and Development of software to predict failure of any system based on multivariate data, signature and patterns, Computer and technology services provided by the software to analyse various parameters from data sets, create working pattern and identify anomalies, Developing software technology based on the identified data to detect possible future based on research of anomalies of Component or whole system. |
| Publication | In Journal No. 2169 |
| Status | Unknown |
| Applicant: | ZASTI INDIA PRIVATE LIMITED |
| Applicant Address | 5th Floor, New building, C- Block, IIT Madras Research Park, Kanagam Road, Taramani, Chennai- 600 113 Service Providers |
| Jurisdiction | MUMBAI |
| Agent | BHUMI JOSHI |
| Agent Address | A wing, 404, Dheeraj Presidency, M.G Road, Kandivli (West), Mumbai- 400 067 |
Frequently Asked Questions
Who is the owner of trademark ZaaS? ▾
The trademark application number 5542378 is owned by ZASTI INDIA PRIVATE LIMITED.
Which class does trademark ZaaS belong to? ▾
Trademark application number 5542378 is filed under Class 42, which relates to the specified goods and services.
Who is the trademark agent for application 5542378? ▾
The trademark agent associated with application number 5542378 is BHUMI JOSHI.
Was trademark ZaaS published in the journal? ▾
Yes, trademark application number 5542378 was published in Journal No. 2169.
What is trademark ZaaS? ▾
Trademark application number 5542378 relates to "Design and Development of software to predict failure of any system based on multivariate data, signature and patterns, Computer and technology services provided by the software to analyse various parameters from data sets, create working pattern and identify anomalies, Developing software technology based on the identified data to detect possible future based on research of anomalies of Component or whole system.".
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