AI Engineers and builders using xpander.ai to start new autonomous agent developement project or to add backend to their existing agent using the following components:

Agentic Tools

Pre-built connectors to SaaS systems and tool generation from API specs

Agent Graph System

Control autonomous agents with precise boundaries

State Management

Scale AI state machines to handle thousands of concurrent users

Human Interfaces

Trigger agents from Slack, Teams, Web UIs, or programmatically

Rapid Development

Build and iterate on agents in minutes, not weeks

Enterprise-Grade Security

SOC 2 compliant with granular access controls

​
Quick Demo

​
Getting started

Build AI agents faster by focusing exclusively on agent logic rather than infrastructure
Basic Agent Loop
# Get your agent
agent = xpander.agents.get(agent_id=os.getenv("XPANDER_AGENT_ID"))

# Manage AI state with a single API (is_finished)
while not agent.is_finished():
    # Get LLM response
    response = llm_provider.chat.completions.create(
        model="gpt-4.1",
        messages=agent.messages,  # Auto-translate messages object between frameworks
        tools=agent.get_tools(),  # Auto-translate tools object between frameworks
    )

    # Extract tool calls from the AI response
    tool_calls = agent.extract_tool_calls(
        llm_response=response.model_dump()
    )

    # Securely run the AI choices in xpander cloud after validating generated payloads
    # Auto-enforce API Rules and dependencies
    agent.run_tools(tool_calls=tool_calls)

# Asynchronously load the agent result for long-running multi-step tasks
task_result = agent.retrieve_execution_result()