SaaS
A service model where software is subscribed to and used over the internet as needed. It is a cloud-based approach that allows users to instantly utilize the latest AI features through a web browser or API without separate installation or server setup.
Detailed explanation
Why It Matters in Tool Selection
When adopting AI tools, the SaaS model converts capital expenditures (CapEx) into operating expenses (OpEx). Since AI technology evolves very rapidly, receiving real-time updates through SaaS, rather than building models in-house, is advantageous for reducing technical debt.
What to Check
- Data privacy: Whether the entered data is reused for model training
- Security compliance: Whether it holds international security standard certifications such as SOC2, ISO27001, etc.
- Pricing structure: Whether it is user-based (seat-based) or AI usage-based
- Scalability: Whether it seamlessly connects with existing work systems through API integration
Examples
Typical examples include productivity tools like Notion AI, design tools like Canva, and chatbot services like ChatGPT Plus. These services provide high-performance AI features directly in the browser simply by paying a subscription fee, without requiring users to maintain separate AI servers.
Confusing Terms
IaaS
A model that only rents out virtualized physical infrastructure such as servers and storage (e.g., AWS EC2)
PaaS
A model that provides platform and tool environments needed for app development (e.g., Google App Engine)
On-premise
A method where software is directly installed and operated on a company's own physical servers rather than in the cloud