andibase Overview

andibase is a purpose-built platform for humans and AI agents to collaborate. It provides the core building blocks for AI agents to build and operate workflows, plus flexible interfaces for humans to connect, collaborate, and operate with security, monitoring, and auditability.

What it is

An open workspace to build, deploy, and operate AI apps and workflows in the cloud without manually wiring together databases, storage, APIs, permissions, keys, domains, and operational layers.

The simplest way to put AI apps and workflows into production in the cloud, with primitives that are ready to operate while staying open and easy to integrate.

Who it's for

Teams and builders who want to move from local experiments or isolated hacks to real workflows that are shared, auditable, and stable, without having to worry about infrastructure.

Why it exists

Most of the core tools behind digital work were designed for human users, not workflows operated by models. Cloud and productivity workspaces are powerful, but they still create too much friction for this use case.

Core principles

1. AI-native human-agent collaboration: Built from the ground up for humans and agents to work together. The core primitives make collaboration natural, and provide the simplest and most powerful way to build, deploy & operate real workflows with agents.

2. Frictionless, open, and ecosystem-ready: Designed to be the simplest and most accessible way to connect, extend, import, export, and integrate, so workflows can run across the tools and systems you already use.

3. Powerful and flexible: Composable building blocks let you model and automate a wide range of workflows, from simple tasks to complex operational processes, without forcing you into rigid patterns.

4. Reliable, secure, and auditable at scale: Made for real operations, with the controls and guarantees teams need to run critical workflows confidently: security, permissions, visibility, history, and rollback.

Trade-offs

1. Building blocks over specialized solutions: andibase is built from general-purpose primitives. For narrow categories with deeper requirements, specialized products are often the better answer and should be integrated.

2. Flexibility over maximum efficiency: Composable blocks unlock range and speed. For extreme performance & guaranties at scale or infrastructure-heavy workloads, dedicated systems are usually a better fit.

3. Simplicity over feature completeness: andibase prefers strong defaults and extensibility over endless built-in features. For unusual needs, extensions, integrations, or custom code are often the right path.

4. Orchestration over intelligence ownership: andibase is the layer for running workflows with humans and agents. For the intelligence itself, the right answer is often the best external model or specialized agent system.

Comparison with other solutions

Local tools are useful for prototyping. andibase is the cloud layer for sharing, integrating, and operating those workflows with the controls teams need.

Where it lives

Local tools

Lives on a local machine.

andibase

Lives in the cloud.

Best fit

Local tools

Great for prototyping, fast iteration, and working locally.

andibase

Built to move those workflows into shared environments and operate them in production.

Collaboration

Local tools

Harder to share context, access, and state across multiple people or agents.

andibase

Multi-user, shareable, and designed for human-agent collaboration.

Integrations

Local tools

Integration and operations rely more on scripts, manual setup, and separate pieces.

andibase

Connected through APIs, webhooks, and events as a first-class foundation.

Models and agents

Local tools

Usually depend more on the local environment and on how each tool handles integrations.

andibase

Lets you use any AI model or provider and works with any agent built on andibase.

Operations

Local tools

Do not come with permissions, auditability, observability, or events as core primitives.

andibase

Comes with permissions, logs, policies, and enterprise-ready operations from the start.

	Local tools Claude Code, Codex, etc.	andibase Cloud platform for agents and humans
Where it lives	Lives on a local machine.	Lives in the cloud.
Best fit	Great for prototyping, fast iteration, and working locally.	Built to move those workflows into shared environments and operate them in production.
Collaboration	Harder to share context, access, and state across multiple people or agents.	Multi-user, shareable, and designed for human-agent collaboration.
Integrations	Integration and operations rely more on scripts, manual setup, and separate pieces.	Connected through APIs, webhooks, and events as a first-class foundation.
Models and agents	Usually depend more on the local environment and on how each tool handles integrations.	Lets you use any AI model or provider and works with any agent built on andibase.
Operations	Do not come with permissions, auditability, observability, or events as core primitives.	Comes with permissions, logs, policies, and enterprise-ready operations from the start.