Today we officially opened Squadbase, a cloud platform focused on the safe, internal operation of AI applications.

Push code written in Streamlit, Next.js, LangChain, Mastra, or the Vercel AI SDK to Git and, within minutes, your app will be live at an internal-only URL. Behind the scenes, user authentication, RBAC, audit logs, and usage analytics are all wired up automatically. Anyone can build line-of-business apps, and once deployed, those apps keep improving through AI. That vision is the heart of Squadbase.

Why We’re Building Squadbase

Our story began seven years ago. As a software vendor integrating machine-learning technology into real-world projects, we watched AI and data create enormous business impact for Japanese enterprises.

When ChatGPT appeared in 2022, we heard the unmistakable sound of a tooling revolution. A new era had dawned in which anyone could craft code-based AI apps tailored to their own workflow. We concentrated on data-driven use cases and created Morph, a framework for building AI apps with Python and Markdown.

While building a hosting platform for Morph, we realized the cloud foundation we had created would also serve other frameworks just as well.

After the code is written, one challenge always remains—delivering it safely and improving it continually—and that burden falls on developers no matter which framework they choose. We became convinced the world needed a framework-agnostic cloud dedicated solely to AI-app delivery.

Why a New Cloud Platform Is Necessary

AI departments are springing up everywhere, and small teams are now churning out internal apps at speed. That’s a wonderful change—yet the more apps you ship, the bigger the operational mountain grows.

A single architecture diagram that fits on one page sprawls into twenty AWS or GCP services in the console, and every new deployment adds another page to the run-book. Delivering often proves harder than building.

• Security comes first. An app holding production data and private-LLM tokens can leak critical information if access control is loose.
• Maintenance costs follow. CI/CD, logging, analytics, and feedback must be rebuilt for every project; once you have a dozen apps, operations staff are overwhelmed.
• The feedback loop stalls. An app cannot evolve if usage data never reaches its developers.

Squadbase exists solely to untangle this three-fold knot.

The moment you push to Git, a pipeline runs; when deployment finishes, auth and RBAC are active and a dashboard is already plotting execution and access logs. A comment box slips into the corner of your app, and every note funnels into GitHub Issues. In the near future, AI will even fix those issues automatically. Anyone can bring ideas, craft the ideal app, and leave the heavy lifting backstage to Squadbase—that’s the world we imagine.

Problems We Solve

Squadbase shoulders the painful parts and delivers secure infrastructure for organizational AI apps, giving developers best practices for security, RBAC, logging, analytics, and feedback through a simple workflow.

Security & Governance

From the moment an app is deployed, user authentication is active and the app is private by default. Project-level roles and TLS 1.2 are configured automatically.

CI/CD & Observability

Connect GitHub or GitLab and a pipeline is generated on the spot; deployments finish in about 3 minutes. Execution and access logs are searchable and visualized in the dashboard.

User Analytics & Feedback

A comment box is injected automatically, and both usage metrics and user feedback stream straight to the dev team, keeping the improvement cycle turning naturally.

Framework-Agnostic Delivery

Whether it’s Streamlit, Next.js, or LangChain, drop in a squadbase.yml or Dockerfile and the deployment flow is identical.

Autonomous Optimization (Coming 2025)

Logs will be analyzed by AI, which will suggest prompt tweaks and resource allocations automatically.

Our platform brings the next-generation developer experience to internal app development.

Why Now?

Teams are pulling every lever to harness AI for work. Dedicated “AI divisions” are multiplying, and full-stack frameworks like Streamlit and Next.js keep gaining ground because low-code tools can’t provide the required customization.

Code-generation models are evolving on a weekly cadence. Over the next twelve months, coding AI will make a quantum leap, triggering an explosion in the number of AI apps—and with it, a rising need for robust delivery platforms. That is why we must act now.

Frequently Asked Questions

— How is Squadbase different from Vercel or Amplify?
Deployment targets. Squadbase is designed for internal use and puts SAML/OIDC integration and fine-grained RBAC at its core. Public-facing PaaS offerings were built for a different purpose.

— Do you have security certifications?
Yes. We have passed a SOC 2 Type I audit.

— Is there a free plan?
You can run up to five apps with up to five team members for free. For paid tiers, see our pricing page.

— Can I migrate an existing app easily?
Absolutely. Add a squadbase.yml or Dockerfile and connect your repo. Dedicated support is available; see the docs for details.

Ready to Try?

Sign in with your GitHub account at squadbase.dev—your first deployment takes less than five minutes!