
Squadbase
Internal AI Apps: Fast, Secure, Performant

Description
Squadbase is a development platform designed for creating and deploying internal AI applications efficiently and securely. It provides a Python framework that allows users to launch projects quickly and integrate various Python and React packages for customized development. Users can connect to business data stored in sources like BigQuery, Snowflake, PostgreSQL, Salesforce, and more, using built-in data connectors with fine-grained access controls.
The platform facilitates building custom AI processes using LLM APIs and creating interactive user interfaces with pre-made components or Markdown. Deployment happens within a secure, non-public environment accessible only to the team via URL, featuring built-in Role-Based Access Control (RBAC) and SOC2 Type 1 compliance. Additional features include cloud-based VS Code integration, Git management, scheduled execution for data workflows, and options for local LLM deployment using Ollama.
Key Features
- Python Framework: Launch projects quickly and extend with Python/React packages.
- Secure Hosting Environment: Deploy apps in a secure, team-only environment.
- Built-in Data Connectors: Connect securely to databases (BigQuery, Snowflake, PostgreSQL) and SaaS tools (Salesforce, Intercom).
- Role-Based Access Control (RBAC): Manage user permissions with built-in roles.
- Custom AI Integration: Build workflows using LLM APIs and ML models.
- Markdown UI Builder: Create interfaces using Markdown or pre-made components.
- CI/CD Integration: Streamlined deployment pipeline.
- Git Management: Manage application code via Git repositories.
- Scheduled Execution: Automate SQL and Python data processes.
- Local LLM Deployment: Support for deploying LLMs locally using Ollama (Pro plan).
- Security Compliance: Adheres to SOC2 Type 1 standards.
Use Cases
- Developing custom internal AI tools for teams.
- Building secure data processing applications connected to internal databases.
- Creating interactive dashboards using business data and AI models.
- Deploying AI-powered workflows for specific team needs.
- Automating data tasks with scheduled Python/SQL scripts.
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