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How Much Does It Cost to Develop an AI-based SaaS Product

In today’s tech-savvy world, artificial intelligence (AI) plays a crucial role in revolutionizing businesses across industries, helping them get innovative solutions and driving efficiency. One such AI-based solution that has completely transformed the modern business world is software-as-a-service (SaaS). SaaS applications are run in the cloud and can be accessed through desktops, web interfaces, and mobile applications with an active internet connection.

Today, SaaS products are witnessing rapid growth and massive demand in the market due to their ability to provide scalable and efficient solutions. According to Statista, the global SaaS market is estimated to be worth $197 billion in 2023 and reach $232 billion by 2024. 

With the ever-growing popularity of SaaS products, enterprises often ask, “How much does it cost to develop an AI-based SaaS product?” 

Designing and developing a SaaS product without having a clear idea of product scope, requirements, and other essential features can increase the time and effort required in product development. It can result in a significant increase in its development costs also.

Therefore, it is vital to define your product objective and understand its tech stack, scalability, software development services, features, and other essential elements. Having a deep understanding of these vital components will help optimize the SaaS product development cost.

This blog will give a comprehensive overview of developing an AI-based SaaS product based on different factors involved in the process.

Understanding AI-Based SaaS Products

For efficient cost optimization, it is imperative to understand what AI-based SaaS products entail. SaaS products leverage emerging AI technologies, such as machine learning, computer vision, natural language processing, and data analytics, which help deliver intelligent and automated solutions to end users.

A successfully developed SaaS product tends to offer multiple benefits to users, like predictive analytics, chatbots, automated data processing, recommendation systems, and personalized user experiences.

With so many use cases and advantages of leveraging SaaS products, its market size is significantly increasing with each passing day. Accordingly, worldwide end-user spending in the SaaS industry is forecasted to grow at a rate of 21.7% from $491 billion in 2022 to $597.3 billion in 2023 – as per the latest report by Gartner.

SaaS Product Development Cost

Providing an exact cost to develop a SaaS product is quite a challenging and intimidating procedure due to the various factors involved in the process. However, to give you a rough idea, a SaaS MVP product costs between $15,000 to $100,000. An average AI-based SaaS product development cost ranges somewhere between $50,000 to $200,000. For more advanced, feature-rich, and complex products, the cost can upsurge $500,000 or more. 

Here, it is imperative to keep in mind that development cost is just the initial phase of the long journey. There is an ongoing expense for product maintenance, support, and updates. Hence, the cost of maintenance and upgrades should also be taken into account when budgeting for an AI-based SaaS product. 

To get a detailed insight into SaaS product development, let’s delve deeper to understand various factors that contribute to development costs. 

Factors Affecting the AI-Based SaaS Product Development Cost

As said above, there are various factors that contribute to SaaS product development. Here is a comprehensive analysis of the crucial factors affecting the development cost.

Product Complexity

We should always keep in mind that the more complex the product is, the higher it will cost. Complexity consists of different features, functionalities, modules, and challenges that an AI development company faces while building the product. 

Prime features like data security, customization, payment integration model, etc., significantly contribute to the SaaS software development time, effort, and resources, thus leading to an increase in cost.

Depending on the level of complexity, SaaS products can be categorized into four types: Micro SaaS, Basic SaaS, Average SaaS, and Basic SaaS. Based on these categories, here is an estimated cost breakdown.

Complexity Average Cost
Micro SaaS $20,000-$30,000
Basic SaaS $40,000-$50,000
Average SaaS $60,000-$80,000
Complex SaaS $150,000-$200,000

Development Stage

SaaS product development is a complex and time-consuming process involving various stages and steps. Ideation, planning, UI/UX designing, programming, MVP development, testing, and deployment are the most important phases contributing to a successful product launch. Each of these stages plays a crucial role in defining the timeline and cost of SaaS product development.

Let’s have a rough estimate of each phase to understand the cost breakdown.

Development Stage  Average Cost
Planning and MVP Development $40,000-$80,000
UI/UX Design $5,000-$10,000
Front End Development $20,000-$50,000
Back End Development $30,000-$80,000

Product Type

SaaS product development cost also varies depending on the application/software category you want to build. Depending on your business domain and industry requirements, your SaaS solution will have different requirements and objectives. Thus, they are designed with dissimilar features and tech stacks, accordingly taking different time and cost in development.

Let’s bifurcate the SaaS product development cost of some popular types of SaaS solutions:

Types of SaaS Solutions Average MVP Price (USD)
Accounting $70,000 – $100,000
ERP $120,000 – $150,000
Email Marketing $70,000 – $80,000
Project Management $80,000 – $90,000
HRM Solutions $30,000 – $80,000
CMS and E-Commerce $100,000 – $150,000
Communication Platform $20,000 – $100,000
Payment Gateways $80,000 – $120,000

Geographical Location

The location of your chosen AI software development company also plays a crucial role in deciding the SaaS product development cost. The cost differs across regions and continents. For instance, the developers located in the US typically cost higher than that in Australia, the UK, or Asia.

Let’s have a view at the cost breakdown of the SaaS solution as per the geographical locations of developers:

Geographical Region Average Cost 
US $170,000 – $180,000
UK $140,000 – $150,000
Eastern Europe $50,000 – $60,000
Western Europe $90,000 – $100,000
Australia $110,000 – $120,000
Asia $40,000 – $50,000

Developer Type

Lastly, the cost to build a SaaS product heavily depends on the kinds of developers you partner with for your project development. If your company is based in the US, hiring local developers might cost you hire than an offshore development team. Also, your in-house team might lack the essential skill of development, and hiring new staff or training the existing ones can exceed the overall cost and also hamper the other crucial operational processes. 

Therefore, the ideal choice is outsourcing an AI development company based in South Asian countries like India. Here you can find proficient developers to get quality work and cost-effective solutions.

Depending on the developers’ type, here is a cost breakdown for SaaS product development:

Developer Type Average Cost
Freelancers $50,000 – $80,000
Local Agency $170,000 – $180,000
In-house $1200,000 – $1500,000
Outsourcing (Contract) Agency $80,000 – $100,000

How do you maintain AI-based SaaS product performance?

Ensuring the consistent performance of an AI-based SaaS product after deployment is critical to user satisfaction and long-term success. Proper maintenance and monitoring practices can help detect issues early, optimize system performance, and implement enhancements. Here are key strategies for maintaining the performance of AI-based SaaS products:

  • Regular System Health Checks
    Schedule regular health checks to monitor the performance of the AI model and underlying infrastructure. This can help detect any bottlenecks or downtimes early, ensuring prompt responses to any potential issues.
  • Performance Monitoring Tools
    Invest in performance monitoring tools that track metrics such as latency, server uptime, and error rates. Tools like New Relic, DataDog, or custom monitoring solutions can offer real-time insights to keep the system running smoothly.
  • AI Model Updates
    AI models require periodic updates to stay accurate and relevant. Set a schedule for retraining models with new data, especially if the model’s performance degrades over time due to changing data patterns or evolving market conditions.
  • Scalability Testing
    Test the SaaS product’s ability to handle increased loads by conducting scalability testing. This practice ensures that the infrastructure can expand as user demand grows without compromising speed or functionality.
  • User Feedback Integration
    Collect user feedback regularly and integrate it into the maintenance roadmap. Addressing user-reported bugs, performance lags, or feature requests can greatly improve the overall experience and help retain users.
  • Security Patch Updates
    Regularly update security patches and address vulnerabilities, especially those affecting AI components and data storage. Cybersecurity breaches can severely impact performance and trust in the product, so prompt and proactive updates are essential.

With these practices, you can maintain the optimal performance of your AI-based SaaS product, ensuring it meets user expectations and adapts to changing demands over time.

Final Thoughts

Getting an estimate of the cost to develop an AI-based SaaS product requires a comprehensive understanding of the various factors involved in the process. And while getting an exact figure of the SaaS product development cost is intimidating, it is good to partner with a trusted AI development company to get an accurate cost idea within your budget. On average, an AI-based SaaS product costs between $50,000 to $200,000, depending on the factors mentioned above.

Nestor Gilbert

By Nestor Gilbert

Nestor Gilbert is a senior B2B and SaaS analyst and a core contributor at FinancesOnline for over 5 years. With his experience in software development and extensive knowledge of SaaS management, he writes mostly about emerging B2B technologies and their impact on the current business landscape. However, he also provides in-depth reviews on a wide range of software solutions to help businesses find suitable options for them. Through his work, he aims to help companies develop a more tech-forward approach to their operations and overcome their SaaS-related challenges.

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