OSMI IT Implemented 8 AI Agents: How a Pizzeria Delivered 15% More Orders with the Same Staff

At the OSMI IT pizza chain, before the implementation of AI agents, each call center operator processed 40-50 orders per hour. After the company implemented eight AI agents, productivity increased, and the same staff can now process 15% more orders, reducing personnel costs by 20% and cutting order processing time by 25%.

In the restaurant business, especially in delivery, each operator is both a growth point and a bottleneck. Too much routine, too many distractions, too much human factor directly affecting service speed and quality. This costs hours, money, and lost customers, but this pain is solvable, and a solution is now available to any business.

How the Process Looked Before AI Agents

Before the implementation of AI agents, the order processing in OSMI IT pizzerias was entirely reliant on live operators. This meant that every step, from answering a call to sending the order to the kitchen and coordinating delivery, required direct human involvement. Operators faced a constant stream of calls, the need to quickly navigate menus, promotions, addresses, and handle changing customer requests.

During peak hours, when the number of orders surged, operators worked at their limits. This led to increased waiting times for customers, errors in orders due to haste, and consequently, a decrease in customer satisfaction and loss of potential profit. The productivity of one operator was 40-50 orders per hour, a ceiling that could not be broken without increasing staff.

Why Standard Automation Fell Short

OSMI IT already used standard automation systems, such as CRM and POS systems, but they did not solve the key problem — the need for extensive manual labor at the order intake and processing stage. These systems helped structure data and manage logistics but could not independently interact with customers, answer questions, accept changes, or handle specific requests.

What was needed was not just to speed up individual operations, but to create an intelligent system that could fully or partially replace humans in routine but critical tasks. This led the company to the idea of implementing AI agents capable of handling communication and initial order processing.

How AI Agents Were Designed for the Pizzeria

OSMI IT decided to implement eight specialized AI agents, each responsible for a specific area of work. This allowed for the creation of a flexible and scalable system capable of handling various types of requests and effectively interacting with customers and internal systems.

• Order Taking Agent. Primary task: answer calls, recognize speech, clarify order details, suggest additional items, and place orders in the system.
• Order Confirmation Agent. Automatically called customers to confirm order details, addresses, and delivery times, minimizing errors.
• Menu and Promotions Agent. Answered customer questions about dish ingredients, current promotions, and special offers.
• Delivery Management Agent. Coordinated couriers, tracked order statuses, informed customers about delays, and re-routed orders when necessary.
• Feedback Agent. Collected customer feedback after delivery, analyzed it, and forwarded information to relevant departments.
• Queue Management Agent. Optimized the distribution of calls between live operators and AI agents to minimize waiting times.
• Training Agent. Analyzed dialogues of live operators and AI agents, identified best practices, and suggested improvements for scripts and algorithms.
• Analytics Agent. Collected data on the performance of all agents, order processing times, errors, and customer satisfaction for further analysis and optimization.

This architecture allowed for a comprehensive solution where each agent performed its specific function, yet all worked in conjunction, ensuring the smooth operation of the entire system.

Implementation and Team Adaptation

The implementation of AI agents proceeded in stages. First, agents for order taking and confirmation were launched, as they were the most critical for increasing productivity. The company conducted training for operators, explaining how AI agents would work and how they could focus on more complex, non-standard requests requiring human intervention.

A crucial aspect was establishing clear protocols for task handover between AI agents and live operators. If an AI agent could not process a request (e.g., the customer asked a too complex or unusual question), it automatically transferred the call to an available operator. This ensured a smooth transition and avoided negative customer experiences.

The implementation took about three months, including testing and fine-tuning. The team quickly adapted, as AI agents significantly reduced the routine workload, allowing operators to engage in more interesting and complex tasks.

Implementation Results

The implementation of eight AI agents enabled OSMI IT not only to significantly increase productivity and reduce operational costs but also to improve customer service quality. The 15% increase in processed orders with the same staff means the company could scale its business without a proportional increase in personnel costs. The 25% reduction in order processing time led to faster delivery and, consequently, higher customer satisfaction, confirmed by a 10% rise in this metric.

The 5% reduction in order error rate is also a significant indicator, as every error means not only a dissatisfied customer but also additional costs for rework and re-delivery.

How to Implement This in Your Business

The OSMI IT case demonstrates that a comprehensive implementation of AI agents can radically transform operational processes. If your business faces similar challenges, here's where you can start:

• Identify Routine Operations. Find tasks that consume a lot of your employees' time, repeat daily, and have clear execution algorithms. These are ideal candidates for AI agent automation.
• Start with "Quick Wins". Choose one or two areas where an AI agent can deliver immediate and obvious results, such as taking simple orders or confirming bookings. This helps the team see the value and adapt faster.
• Design Agents for Specific Tasks. Don't try to create one universal agent. Break down tasks into smaller ones and create specialized agents for each, as OSMI IT did.
• Ensure Seamless Integration. AI agents should be integrated into existing systems and workflows to minimize discomfort for employees and ensure smooth operation.
• Don't Forget Training and Support. Train employees on how to work with new tools and create a support system so they can get help with any questions.

If this case sounds like what's happening in your company, our manager can help: he'll analyze your business and niche for free and point out where an AI agent would bring a real result in your case. Message the manager