xpander.ai’s Agent Graph System makes AI agents more reliable, gives them info step-by-step
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Israeli startup xpander.ai has introduced the Agent Graph System (AGS), which it says is a major new approach to building more reliable and efficient multi-step AI agents based on underlying AI models such as OpenAI’s GPT-4o series.
The goal is to redefine how AI agents interact with APIs and other tools, making advanced automation tasks more accessible to organizations across industries.
Function calling, the backbone of most AI agent workflows, enables models to interact with external systems to perform tasks such as fetching real-time data or executing actions.
However, these interactions often falter when faced with complex API schemas or unpredictable responses, leading to inefficiencies and errors.
xpander.ai’s Agent Graph System introduces a structured solution to these challenges by using a graph-based workflow that guides agents through appropriate API calls step by step.
