Multi-Tenant CRM with Intelligent Scheduling
Rohini Ram Kulkarni
, Bhagyashri Tupere
Customer Relationship Management (CRM), Multi-Tenant Architecture, Intelligent Scheduling, Automation, Artificial Intelligence, Cloud Computing
Customer Relationship Management systems are very important for businesses today. They help companies manage sales, marketing and customer service in one place. Because many businesses are now online there is a big need for Customer Relationship Management systems that can handle a lot of users and data without being too expensive. To solve this problem many companies are using something called -tenant architecture, where one application can be used by many different organizations at the same time. This system is designed to be safe and secure so each organizations data is protected.
We have created a Customer Relationship Management system that uses artificial intelligence to make decisions and automate tasks. This system is designed to be flexible and customizable so it can be used by different types of businesses. We looked at Customer Relationship Management systems, like Salesforce, Zoho CRM and HubSpot CRM and we found that they have some limitations. They can be expensive hard to use and not very flexible. Our system is designed to be more efficient and cost-effective and to provide security and scalability.
We used a combination of intelligence and automation to create a system that can handle tasks automatically without needing human intervention. This includes things like scheduling, follow-ups and data handling. Our system also uses data and user availability to make decisions so it can optimize schedules and workflows.
"Multi-Tenant CRM with Intelligent Scheduling", JETNR - JOURNAL OF EMERGING TRENDS AND NOVEL RESEARCH (www.JETNR.org), ISSN:2984-9276, Vol.4, Issue 6, page no.a322-a327, June-2026, Available :https://rjpn.org/JETNR/papers/JETNR2606043.pdf
Volume 4
Issue 6,
June-2026
Pages : a322-a327
Paper Reg. ID: JETNR_234983
Published Paper Id: JETNR2606043
Downloads: 00077
Research Area: Science and Technology
Country: Pune, Maharashtra, India
ISSN: 2984-9276 | IMPACT FACTOR: 9.87 Calculated By Google Scholar | ESTD YEAR: 2023
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.87 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: RJPN (IJPublication) Janvi Wave
