The chaos of a peak lunch hour in a commercial kitchen often spills over into the logistics chain. A restaurant owner, rushing between stations, sends a frantic SMS to their supplier. Another scribbles a hurried note on a napkin and snaps a photo. A third leaves a clipped voice memo. For the distribution manager, these fragments of intent arrive as a disorganized deluge of unstructured data across emails and messaging apps. The only way to move these orders into the corporate Enterprise Resource Planning system is through manual entry, a tedious process where a single typo or a missed line item creates a ripple effect of operational failure and lost revenue.

The Scale of AI Integration at Choco

Choco, a platform dedicated to modernizing food and beverage distribution, operates at a scale that makes manual processing impossible. The company currently connects 21,000 distributors with 100,000 buyers across the United States, United Kingdom, Europe, and the GCC region. To manage this volume, Choco has integrated the OpenAI API to handle more than 100 million orders annually. The sheer computational load is immense, with the production environment consuming over 1 trillion AI tokens to maintain its operational flow.

Central to this architecture is the OrderAgent, a specialized tool designed to convert multimodal inputs into structured data. Whether the input is an email, an SMS, a photo of a handwritten list, or a digital document, the OrderAgent parses the unstructured content and transforms it into a format that can be injected directly into an ERP system. Complementing this is the VoiceAgent, built on the OpenAI Realtime API. This agent automates phone orders with a latency of less than 1 second, allowing the system to handle natural voice interactions and accept orders even outside of standard business hours.

The impact of these deployments is quantifiable. Choco reports an 80% reduction in manual order entry tasks. More significantly, the company has doubled the productivity of its sales teams without the need to hire additional personnel. The decision to utilize OpenAI was driven by the specific requirements of the F&B industry: the need for high-performance multimodal capabilities, the ability to generate structured outputs, and the reliability required for large-scale enterprise deployment.

From Workflow Software to Execution Infrastructure

For decades, the standard for B2B software was the workflow management model. In this paradigm, software provided the digital forms and buttons that humans used to move data from one place to another. The human remained the primary engine of execution, reading a memo and typing it into a database. Choco has fundamentally inverted this relationship. By leveraging the OpenAI SDK and API, the platform has shifted from being a tool that manages a workflow to an infrastructure that executes the work itself.

This transition was made possible by integrating several core AI capabilities into the underlying infrastructure. Speech-to-Text handles the initial ingestion of audio, while Embeddings allow the system to understand the semantic context of diverse requests. The critical bridge to action is Function Calling, which enables the LLM to trigger external functions within the ERP, turning a conversational request into a hard database entry. This means the user no longer needs to adapt to the software's interface; the software adapts to the user's natural method of communication.

Maintaining accuracy in a high-stakes supply chain requires more than just a powerful model. Choco implemented a rigorous evaluation framework based on ground-truth datasets to ensure that the AI's structured output matched reality. This was paired with continuous monitoring and A/B testing to refine the agents' performance. An unexpected result of this technical shift is the evolution of the user role. Non-engineers within the organization have stepped into the role of agent orchestrators, designing and managing how these AI agents collaborate to solve complex logistics problems.

The competitive advantage in enterprise software is no longer found in the elegance of the user interface or the convenience of the dashboard. The new frontier is the ability to convert unstructured, real-world data into precise, executable commands with minimal human intervention.

This shift marks the end of the era where software simply records what humans do and begins the era where software does the work.