Changelog

We’re excited to announce the new Deploy to Squadbase button, which lets you deploy any GitHub repository with a single click. One press handles the entire flow—clone, build, set environment variables, and go live on Squadbase. OSS maintainers can spin up instant sandboxes for newcomers, while internal teams can share apps with non-engineers without ever touching the CLI.

Snippets

You can add various URL query parameters to the Deploy to Squadbase button to control and customize the deployment experience for users, depending on your project's requirements.

Use the snippets below in your Git repositories or your dashboards for users to deploy.

[![Deploy to Squadbase](https://app.squadbase.dev/button.svg)](https://app.squadbase.dev/new/clone?repository-url=https://github.com/username/repo-name)

Highlights

• Drop a single markdown / HTML badge into a README, blog, or dashboard
• Configure the user flow with URL parameters such as project-name, subdomain, env-var-keys, root-path, and config-path
• Works with monorepos and private repositories accessible to Squadbase
• Ideal for OSS demos or sharing internal tools with non-engineers

→ For the full parameter list and advanced options, see the developer docs.

Squadbase now supports API Key authentication for accessing your deployed applications. Previously, while we supported secure app publishing by safely authenticating full-stack frameworks like Streamlit and Next.js, implementing server-side applications with frameworks such as FastAPI required separate deployments to AWS or Google Cloud. This was a challenge because it prevented users from fully benefiting from Squadbase's deployment experience when they wanted to use common backend processes across multiple applications.

This new feature makes it possible to extract common processes into server-side applications, enabling teams to operate larger-scale applications.

• Access to applications via API Key
• Official support for FastAPI as a framework in squadbase.yml

Of course, deployments using Dockerfiles still allow for the deployment of other server-side frameworks and API Key access.

See the resources below for more details:

• 📖 Blog Post = 📚 API Key Authentication
• 📚 FastAPI Deployment Guide

squadbase.yml for FastAPI

# squadbase.yml
version: '1'

build:
  framework: fastapi
  runtime: python3.11
  package_manager: uv
  entrypoint: main:app

How to Create and Access API Keys

Creating API Keys is straightforward through the Squadbase dashboard. When you create an API Key, you can specify the teams and projects it can be used with in detail. Since you can issue multiple API Keys for a single account, managing them by project ensures secure inter-app communication.

Squadbase now supports multi-environment deployments. Previously, you could deploy to only a single environment, but now we've introduced "Production" and "Preview" environments by default. Additionally, you can create as many custom environments as needed.

Multi-environment deployment is essential when running applications in production. By deploying features from "Staging" or "feature/" branches into separate environments, developers can collaborate easily without worrying about the production environment.

• Link GitHub branches to each environment using exact or wildcard matching.
• Log monitoring is available across all environments.
• User analytics are supported only in the Production environment.
• The Preview environment automatically tracks all branches not linked to any specific environment.

Check out the resources below to get started:

• 📖 Blog Post – Learn how Multi-Environment Deployments simplify your workflow.
• 📚 Documentation – Dive deeper into the setup and capabilities.

Shareable Links per Branch and Commit

From this release onwards, every deployment generates shareable URLs for each environment, branch and commit. Developers can review the impact of their changes in real-time, isolated environments.

You can find each shareable URL in the deployment details section of your deployments list.

AI App Showcase

Squadbase has just launched an AI App Showcase page to highlight the real-world potential of AI-powered applications. Through two sample apps—one built with Streamlit and the other with Next.js—you’ll get a hands-on sense of how AI can transform internal workflows.

Check out the Showcase page here → https://www.squadbase.dev/en/showcase/

Sales Coach AI Chat

A Streamlit-based coaching chatbot that pulls in Markdown files stored in your project’s codebase alongside meeting notes ingested from your CRM (Attio). By feeding it the right context, this chatbot offers tailored advice to salespeople and can be fine-tuned to mirror your own sales processes.

AI Analyst for GA4

A Next.js-powered data-analysis chat app connected to BigQuery with your Google Analytics data. Ask a question, and the AI generates the necessary Python analysis code, runs it safely on a virtual machine, and returns the results in real time. We’ve chosen E2B for the secure execution environment.

Collaborate and Iterate

AI-powered coding agents are ushering in an era of rapid, custom internal app creation—but true impact comes from running those apps in production and continuously iterating on them. To bridge that gap, we’ve built collaboration features for the operational phase.

1. AI-driven scaffolding that jump-starts your app
2. Automated deployments via Git integration
3. Unified runtime and access logs tied to user identities
4. Automated log analysis for actionable insights
5. In-app feedback channels linked directly to developers

In this blog, we share each features in detail.

User Authentication & Role Management

Project roles can be defined per deployed app, using arbitrary strings. These roles are primarily consumed in code to control data access and feature permissions.

Log Collection & Monitoring

Runtime and access logs are automatically collected and made searchable via the dashboard. This enables quick troubleshooting and helps you uncover insights for app optimization.

User Analytics

Squadbase combines its built-in authentication and logging features to analyze and visualize user activity, giving you actionable analytics right out of the box.

Feedback Collection

Squadbase can automatically inject a feedback comment box into deployed apps. Team members can submit feedback directly, and all responses are aggregated in the dashboard for developers to review and act on.

Deploying Next.js on Squadbase

Squadbase supports Next.js, the React-based full-stack web application framework. Vercel is typically the primary hosting environment for Next.js due to its excellent developer experience and high-performance infrastructure. However, Vercel may not always be ideal, especially when restricting public access and providing app access only to specific organizational users. Squadbase launches production-ready infrastructure for internal business apps and all its best practices—with a single click.

In this blog, we share how to make the most of Squadbase’s features when working with Next.js.

Deploying Streamlit on Squadbase

Squadbase supports Streamlit, a framework for building full-stack web applications with Python. Streamlit’s architecture makes UI updates instantaneous and coding straightforward, but production deployment still poses challenges. Standing up a robust environment often means stitching together ten or twenty AWS or GCP services—work that quickly burdens any dev team. Squadbase launches production-ready infrastructure—and all its best practices—with a single click.

In this blog, we share how to make the most of Squadbase’s features when working with Streamlit.

Introducing Squadbase, a New Cloud Platform for AI Apps

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.

In this blog, we share the story behind the development of Squadbase, outline our vision, and explain why a new type of cloud platform is essential in today's evolving technological landscape.

What’s changed

🚀 New Features

• Plan Updates:
  • Free Plan now allows inviting up to 5 users with Viewer permissions.
  • Pro Plan users can invite additional Viewer-permission users for $7 per user.
• Users can now select cloud deployment targets (AWS, GCP) and configure CPU and memory resources.
• Added support for deploying Streamlit applications to Morph Cloud.
• Added support for multipart/form-data in the deployment environment.

🐛 Bug Fixes

• Fixed an issue where certain environment variable updates were not fully applied.
• Fixed a bug causing incomplete log details from the build server.
• Fixed display-related bugs during user invitations.
• Resolved pagination issues when the number of invited application members exceeded a certain limit.
• Corrected an issue where the latest morph-data package version was always selected during builds.
• Fixed a bug causing multiple unintended project creations.

🔧 Improvements

• Enhanced build performance by reducing snapshot frequency during Docker builds.
• Improved user experience when deploying from the dashboard.
• Improved build performance by incorporating frontend code builds directly into Docker build processes.

🚀 New Features

GitHub Login & Automatic Deployment via GitHub Integration

Users can now login to Morph Cloud using their GitHub accounts.

By integrating with GitHub, deployments can be performed automatically without the need for manual setup of CI/CD or using morph deploy via CLI.

Deploying Local LLMs with Ollama

With Ollama, users can deploy local LLMs such as deepseek-r1, llama3.2, phi4, and qwen on the Morph platform.

This allows for the development of AI applications utilizing LLMs while ensuring data privacy and security.

🛠 Maintenance

Stopped New Built-in PostgreSQL Instances

The built-in PostgreSQL feature will no longer be supported after the end of March.

As a result, the option to create new instances has been removed.

What’s changed

🐛 Bug Fixes

• Fixed environment-specific morph deployment failures.
• Fixed binary file response failures in project pages.

What’s changed

🚀 New Features

• Added public release settings for the app
• Added activity display feature for project creation and successful deployment
• Added usage history display feature for built-in DB for Pro plan and above

🐛 Bug Fixes

• Fixed multiple project role inputs
• Fixed developers couldn't invite project members
• Fixed project update time wasn't being updated

🔧 Improvements

• Display member icons in the project list
• Display member icons and available connector icons in project details

What's Changed

🚀 New Features

• Access control for individual members on created projects
• Role assignment for members within projects
• Permission management for using Database/SaaS connectors per project
• Execution log overview with filtering by date and time
• Display of deployment logs
• Fine-grained control for issuing API keys on a per-user basis
• Project search functionality
• Granular permission settings for members within teams

🔧 Improvements

• Enhanced performance and stability through infrastructure upgrades

🛠 Maintenance

• API key issuance changed from team-level to user-level
• Closing of the cloud editor feature
• Closing of the built-in PostgreSQL REST API feature
• Suspension of the job scheduling feature

What's Changed

🔧 Improvements

• In Viewer mode, "Jobs" tab now allows you to check logs for scheduled executions.

🐛 Bug Fixes

• Fixed an issue in the scheduled_jobs section of morph_project.yml where wildcard usage for days in CRON expressions was not working.

Launch Week #2 updates.

LLM Component

New Component for Pages

• Added the LLM component to build LLM apps like chat and text generation. Docs

Added Streaming Function to Python SDK

• Added morph_lib.stream.create_chunk to return function results as a text streaming format. Docs

Link: https://www.morph-data.io/blog/llm-component-launch-week-2

AI Functions

New Helper Functions for AI Integration

Added shorthand functions to simplify AI usage.

• Added text_to_sql function. Docs
• Added text_to_matplotlib function. Docs
• Added text_to_plotly function. Docs
• Added text_to_html function. Docs
• Added text_to_markdown function. Docs

Link: https://www.morph-data.io/blog/ai-functions-launch-week-2

Open-Source Framework

An open-source version of the Morph framework is now available for local use.

Github repository

• Integrated SQL, Python, and Pages frameworks into a single framework.
• Enabled morph serve command to launch data apps in development mode locally.
• Enabled morph sync command to deploy locally built data apps to the cloud.

Link: https://www.morph-data.io/blog/open-source-framework-launch-week-2

Viewer Mode

• Added a mode to display data apps built with Morph in view-only mode.

Link: https://www.morph-data.io/blog/viewer-mode-launch-week-2

Other Updates

New Integrations Added

• Added MS SQL Server as a connection option for SQL Connection.

Scheduled Execution Support

• The scheduling feature, previously available only in the cloud version, can now be configured in the framework via morph_project.yml. Docs

Link: https://www.morph-data.io/blog/other-updates-launch-week-2

This is the first public version of Morph.

Features

• Workspace
• Page
• Morph AI
• Data Connection
• Templates

More details can be found in the Launch Week #1 article.