PaaS Business Model

PaaS stands for the platform as a service. Together with other “as-a-service” models, this model’s basic premise is to offer a solution to the final customer without having to host it on-premise, with complex implementations and large overhead. The PaaS model is a form of evolved cloud computing. The provider, together with virtualization, storage, network, and servers, provides middleware and runtime to the user/customer, which only handles data and applications.

Platform as a Service — IaaS includes servers and storage, networking firewalls and security, and datacenter (physical plant/building). PaaS includes IaaS elements plus operating systems, development tools, database management, and business analytics. SaaS includes PaaS elements plus hosted apps.
Image Source: Microsoft Azure, What Is PaaS?
The different layers of companies built on top of the various “as-a-service” models. From IaaS which is in the middle bottom, to SaaS which also handles the applications for the final user. PaaS is in the middle, as the PaaS provider also manages middleware and runtime, while the user manages data and applications built on top of the PaaS.

PaaS applications and examples

In the PaaS model, the platform that enables the applications’ development is handled by the PaaS provider, where the final user/customer (usually development teams) will handle the application and data itself. Therefore, the PaaS provides a platform where users can develop and deploy their own applications, with the advantage of an agile infrastructure, not hosted on-premise, and therefore faster to implement and more flexible.

Some PaaS providers also include Microsoft Azure, Google Cloud, Amazon AWS, IBM Cloud, where together with the cloud infrastructure (IaaS), the platform to develop and deploy applications on top of the cloud is offered.

This makes it possible for the user/customer of the PaaS provider to only focus on developing and deploying applications, rather than developing the whole infrastructure.

Connected Business Frameworks

Customer Lifetime Value

One of the first mentions of customer lifetime value was in the 1988 book Database Marketing: Strategy and Implementation written by Robert Shaw and Merlin Stone. Customer lifetime value (CLV) represents the value of a customer to a company over a period of time. It represents a critical business metric, especially for SaaS or recurring revenue-based businesses.


AIOps is the application of artificial intelligence to IT operations. It has become particularly useful for modern IT management in hybridized, distributed, and dynamic environments. AIOps has become a key operational component of modern digital-based organizations, built around software and algorithms.

Machine Learning

Machine Learning Ops (MLOps) describes a suite of best practices that successfully help a business run artificial intelligence. It consists of the skills, workflows, and processes to create, run, and maintain machine learning models to help various operational processes within organizations.

Continuous Intelligence

The business intelligence models have transitioned to continuous intelligence, where dynamic technology infrastructure is coupled with continuous deployment and delivery to provide continuous intelligence. In short, the software offered in the cloud will integrate with the company’s data, leveraging on AI/ML to provide answers in real-time to current issues the organization might be experiencing.

Continuous Innovation

That is a process that requires a continuous feedback loop to develop a valuable product and build a viable business model. Continuous innovation is a mindset where products and services are designed and delivered to tune them around the customers’ problems and not the technical solution of its founders.

Technological Modeling

Technological modeling is a discipline to provide the basis for companies to sustain innovation, thus developing incremental products. While also looking at breakthrough innovative products that can pave the way for long-term success. In a sort of Barbell Strategy, technological modeling suggests having a two-sided approach, on the one hand, to keep sustaining continuous innovation as a core part of the business model. On the other hand, it places bets on future developments that have the potential to break through and take a leap forward.

Business Engineering


Tech Business Model Template

A tech business model is made of four main components: value model (value propositions, missionvision), technological model (R&D management), distribution model (sales and marketing organizational structure), and financial model (revenue modeling, cost structure, profitability and cash generation/management). Those elements coming together can serve as the basis to build a solid tech business model.

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