Service-As-Software vs. SaaS: Understanding the Difference and Choosing the Right Model

What Is Service-as-Software?

Service-as-software is a new concept in the AI ecosystem, which aims to redefine traditional software-as-a-service.

Instead of focusing on selling software that can be used to deliver services, service-as-software sells the service itself, which is mainly delivered by AI.

Such an approach deeply integrates AI to ensure better automation, easier scalability, and better cost reduction, thanks to dynamic and intelligent features.

Generative AI plays a huge role in service-as-software advancements, as it helps enable real-time, personalized, and adaptive solutions that improve autonomy and can continuously improve through machine learning.

Service-as-Software vs. Traditional SaaS

Instead of providing software that delivers the service (traditional SaaS), service-as-software sells the service itself.

A typical SaaS model still requires humans to use the software to complete the service themselves. Service-as-software is seen as a dynamic, intelligent, and improved way of delivering autonomous services backed and powered by AI models.

Traditional SaaS:

• Relies on applications that come with a fixed and predefined set of features
• Requires people to use the software to achieve the result themselves
• Has limited customization
• Has a limited personalization capability with no real-time adaptation
• Offers reactive support and requires intervention from service providers
• Offers APIs to integrate with other systems and apps

Service-as-software:

• Provides AI-driven features that improve over time based on user interactions and data analysis
• Can organize workflow, dynamically adapt to changing conditions, and make decisions based on them
• Can execute the entire workflow using autonomous AI Agents
• Improves performance and accuracy by continuously learning from data inputs and user behavior
• Can personalize the experience by analyzing user patterns and preferences
• Can automatically predict and eliminate issues before they become a problem
• Provides customizable solutions tailored to user needs that can make autonomous decisions and take required actions based on changing conditions

There are 5 key differences between SaaS providers and service-as-software:

1. Automation
2. Adaptability
3. User experience
4. Efficiency
5. Scalability

Service-as-software is a superior solution because it continuously learns and adapts, is highly intelligent due to deep AI integration, can provide a highly personalized experience, automates the tasks with proactive support, and is much more scalable.

Traditional SaaS Examples

SalesForce is one of the biggest SaaS companies that provides a suite of customer relationship management tools for sales, service, and marketing.

With their set of tools, businesses can manage customer relationships and automate various processes. However, the actual work still needs to be done by the employees themselves.

With such a SaaS provider, a SalesForce client has to input data into the software, from where the software helps create and organize the workflow to boost productivity.

Another great example is Microsoft 365, which provides cloud infrastructure for productivity software. The suite includes tools like Word, Excel, PowerPoint, and other collaboration tools. Cloud-based SaaS applications are highly convenient and can improve productivity, but they still require people to input data and use the software to achieve its goals.

Service-As-Software Examples

HubSpot is a great example of service-as-software as it employs AI to offer predictive lead scoring, automated email responses, and intelligent chatbots that can provide real-time customer support with automated responses.

Once HubSpot users set up the tool, most of the AI-enabled features are automated and don’t require further human input.

We’ve also recently discussed AI-driven underwriting on our podcast. You’ll notice that the focus wasn’t on AI underwriting assistants, but on AI underwriting.

This perfectly describes the AI-powered underwriting service we deliver. We train AI Agents on the company’s data, documents, and workflow, so they can autonomously perform most of the tasks in organizational workflows.

Some of the results our clients have seen include serving 20x more borrowers, minimizing human errors, reducing operational costs, and enhancing scalability.

The Benefits of Service-as-Software for Businesses

Improved Efficiency

Service-as-software can automate routine and repetitive tasks that otherwise require human intervention such as data entry and reporting.

With AI’s ability to input, update, and manage data across systems, service-as-software boosts efficiency and reduces error and the need for human intervention.

Besides automating tasks, AI can also improve workflows by helping in managing approval processes and tasks. For example, by routing documents for approval based on predefined rules and the company’s data, AI reduces delays and improves turnaround times.

Improved and Automated Decision-Making

Service-as-software, powered by AI, can improve the decision-making process by analyzing data in real time, offer AI-driven insights, but also automatically take action based on changing conditions.

A great example would be a loan underwriting company, where service-as-software can help analyze documents and make data-driven decisions. This way, not only can service-as-software improve decision-making process, but it can also automate it while needing very little to no human intervention.

When certain conditions aren’t met, AI can also make a decision to reject the application, or if unsure, it can send it to a human for review.

Cost Savings

With task automation, service-as-software can save costs by minimizing labor while increasing efficiency.

AI-driven automation can handle data entry, reporting, and workflow management, which optimizes resource utilization. Such use of AI helps reduce operational expenses, as well as reduce waste and idle time.

What once required dozens of employees is now something that an AI agent can automate. While many believe this would lead to job loss, it’s quite the opposite. It allows people to work better by focusing on more complex and important tasks, which can result in getting new and higher-level positions with more responsibility.

Companies can also reduce costs by minimizing errors while providing substantial business growth. Continuous learning capabilities of service-as-software help provide an ongoing improvement of the company’s processes.
‍

This allows companies to cut costs and handle more business at the same time.

Enhanced Customer Engagement

Service-as-software leverages AI to improve customer service and engagement through automated and personalized interactions in real time.

Such personalization can tailor customer offerings based on individual behavior and preferences, resulting in more relevant products and services.

Some of the most known service-as-software models are chatbots and virtual assistants, which can provide 24/7 customer support and resolve queries quickly and efficiently without needing human assistance.

Besides enhanced customer satisfaction, businesses can also benefit from customer feedback. Further analysis of customer feedback can help companies make adjustments to their products and services.

Proactive Problem Solving

A big difference between service-as-software and traditional SaaS is the proactive approach, which allows service-as-software to address and automatically eliminate issues before they escalate. By leveraging AI and machine learning, service-as-software can eliminate potential problems by executing needed tasks, even before companies need to take action.

With recommended preventive measures, companies are automatically free of problems that could lead to potential downtime and expenses.

One of the AI’s strongest advantages is real-time monitoring. For example, AI can analyze operational data to detect unusual patterns and automatically handle issues.

Besides preparing companies to deal with upcoming challenges, proactive problem-solving also helps businesses in the preparation of contingency plans that can improve readiness to handle future problems.

How Multimodal Fits In

Here at Multimodal, we simplify complex middle and back office workflows through purpose-built automation solutions, which deploy as APIs on your infrastructure.

We can help you keep your existing processes and point solutions intact, yet train and fine-tune AI models using your data to ensure better relevancy, precision, and accuracy.

Our AI models are service-as-software solutions that can help:

• Manage your compliance and underwriting workflows
• Automate tasks like risk assessments and policy reviews with unparalleled speed
• Free up time for patient-focused care and strategic initiatives by automating complex healthcare processes
• And more — we work with insurance, banking, and healthcare companies to automate various workflows.

Our AI agents have helped companies automate up to 97% of the workflow, provide a 40x increase in client user base, and achieve an 80% decrease in cost and a 20% increase in revenue.

Here’s what our AI agents can help you with:

• Document AI – Automate your document processing workflows. – Process and classify documents, extract and normalize data, automate repetitive data entry, improve workflow efficiency, simplify document processing and management, and reduce errors in data handling.
• Decision AI – Automate your complex decision-making workflows. – Analyze and verify data, request missing information, make approval decisions in seconds, conduct a thorough analysis of data, and increase accuracy in risk assessments.
• Database AI – Automate your knowledge retrieval workflows. – Retrieve data from databases without code, answer user queries within seconds, empower non-technical employees and users, deliver rapid and effective staff support, provide easy access to insights to improve customer service, and get the most from your data repository.
• Conversational AI – Automate your knowledge retrieval workflows. – Retrieve answers from unstructured documents, extract intelligence from audio to video, speed up informational retrieval, provide accurate answers to company-related questions, and improve response personalization.

Service-As-Software vs. Traditional SaaS: Who Wins?

Service-as-software is a clear winner as it surpasses traditional SaaS by leveraging advanced artificial intelligence to provide greater automation.

As a result, it can automate tasks, make decisions based on changing conditions in real-time, and offer personalized, adaptive, and continuously improved services. With such adaptation, service-as-software integrates real-time data processing, predictive analytics, and advanced autonomy features to provide an automated service that requires very little human input.

Such a dynamic approach is what traditional SaaS lacks, which not only allows service-as-software to provide better advantage but also more flexible, responsive, and automated solutions.

‍

Would you like to try service-as-software and benefit from reduced costs, improved decision-making, and better operational efficiency? Please schedule a 30-minute call with our experts.

We can discuss your needs, find the best way to integrate AI-enabled service-as-software in your workflow and show you how our AI solutions work live.