Introduction

What is Squadbase?

Squadbase is a platform designed to deliver AI applications securely.

Advances in large language models (LLMs) have created a growing need to improve productivity with AI. By combining LLM frameworks and SDKs such as LangChain, Mastra, and the AI SDK by Vercel with full-stack frameworks like Streamlit and Next.js, you can build fully customized AI apps that have a huge impact on day-to-day operations.

The real question is how to deliver AI apps securely. Most AI apps should be shared only with specific stakeholders, because they often access business data or private LLM endpoints. Public cloud hosting services can raise security and data-governance concerns, and configuring a secure infrastructure yourself is a lot of work. You also need logging, usage analytics, and feedback tools just to operate the app.

Squadbase takes that burden off your shoulders, providing secure infrastructure purpose-built for internal AI apps. With a simple workflow you get best practices such as security, role-based access control, log monitoring, usage analytics, and feedback collection.

Squadbase is built by a team with eight years of experience delivering data, ML, and AI projects for Japanese enterprises—organizations with very strict security requirements.

We also develop Morph, a full-stack framework for AI app development.

Why use Squadbase?

Squadbase handles the heavy lifting of AI app delivery so you can focus on building features that improve business outcomes. We believe lowering the cost of building and maintaining internal apps—and maximizing ROI through continuous improvement—is key. To that end, Squadbase brings a modern developer experience to internal-app development with features like:

• Automated CI/CD through Git integration
• Built-in user authentication
• Per-app roles and access control
• Automatic collection and monitoring of runtime and access logs
• Usage analytics
• In-app comment boxes for gathering user feedback