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In several cases where IT executives work towards moving key enterprise applications to the public cloud, their teams struggle or have limited success in their cloud migrations. However, they never give up and they use these lessons to improve their results in subsequent attempts.
If your organization is wanting to modernize mission-critical applications and you’re designing a cloud migration as a locality of this process, you don’t wish to repeat others’ mistakes.
Cloud-based SaaS is relatively a new approach for businesses to provide software solutions on a subscription basis, and it has become one of the most admired industry trends in recent times. According to multiple reports, approximately 85% of small businesses have already invested in SaaS, and it is expected to generate a market share of 105 billion USD in 2020. Before we jump into the development phase of SaaS application, let’s first understand what exactly SaaS is, its advantages, and why so many businesses are tweaked towards it.
In simple words, these are the same applications or software as we use but instead of installing and storing data on our own computer, it stores data on web clouds which can be accessed by anyone having your account credentials. And, these services can be purchased on a monthly or yearly subscription basis just like your Netflix account. This is quite a simple progression, but it offers very useful features and, due to this, many businesses are inclined to invest in a cloud-based SaaS model. If you want to dig further, here are some related terms – IaaS and PaaS that you can opt to explore.
Entrepreneurs, CEOs, CTOs, and IT leaders are generally tasked with choosing the ideal SaaS tech stack. Ultimately, this will be a deal-breaker in the success of your application. You can have a fantastic idea, marketing, and sales team. However, if your SaaS tech stack doesn’t scale, evolve, and continuously transform, you might be ending refactoring your entire SaaS web application every other year. This approach usually results in a waste of time, resources, and money.
A quick look at SaaS communities and questions usually arise about what would constitute the perfect SaaS technology stack. The right answer to this question would be one that includes the combination of language and tools that get the job done.
Businesses are quickly acknowledging the importance of Conversational AI (CAI) to increase their customer engagement and revenues. The question is no longer whether to deploy CAI, but rather which platform to use and how to leverage its capabilities.
In this series, see some insight on important aspects of a conversational AI platform that buyers often overlook. For example, what does language support really mean? What is localization? How do different deployment models impact the TCO? And maybe most importantly – How can the CAI platform not only help me during the first development sprints – but across the entire bot lifecycle?