Introduction

Teams use xpander.ai to build Agents as products. That means they don’t just create one-off automations or single-use scripts. Instead, they use xpander to build AI Agents that are:

Reusable – packaged with functionality that can be leveraged across use cases and teams.
Deployed – running reliably in production, not just in notebooks.
Integrated – accessible via APIs, MCP and A2A, Slack, and more.
Maintained – versioned, monitored, and continuously improved like any software product.
Scoped for others – usable across teams or externally, with clear access and governance in place.

Some examples include:

Simple tool calling Agents: Agents with tools and instructions
Knowledge Agents: Agents with knowledge bases and storage
Reasoning Agents: Agents with memory and reasoning capabilities
Autonomous Agents: Agents that don’t require user interactions and powered by scheduled tasks and events
Multi-Agent Systems: Complex multi-agent systems that work together on achieving tasks
🧠AI Employees: Production-grade agents designed to behave like software-powered teammates and can include all of the above.

Code Examples

from agno.agent import Agent
from agno.models.openai import OpenAIChat

agno_agent = Agent(model=OpenAIChat(api_key="your-openai-key"))
agno_agent.print_response(message="What's your role?")
agno_agent.print_response(message="What did I ask you?")

$ python without_backend.py

User: What's your role?

Agent: I serve as an AI developed by OpenAI, designed to assist with a 
wide range of inquiries and tasks. My role involves providing information, 
answering questions, generating creative content, assisting with 
problem-solving, and offering general guidance across various topics.

User: What did I ask you?

Agent: I'm sorry, but I don't have the ability to recall past 
interactions or questions you might have asked. Can you please 
remind me or ask your question again?

What the Backend Provides

The Backend automatically provides memory, custom instructions, model settings, tools, and storage - all configured through xpander.ai’s platform. All agents in xpander.ai have a complete agent lifecycle with CI/CD pipelines, event triggers that can be configured with Slack, WebUI, MCP, and webhooks - all without infrastructure setup and available out of the box. The Workbench allows you to customize the agent backend and test the agent in real-time.