«Pizza Surgut» Reduced Routine from 7 Hours to 30 Minutes: How 8 AI Agents Transformed the Restaurant Chain's Operations

At the "Pizza Surgut" restaurant chain, manual document processing used to take up to 7 hours a day. Managers spent countless hours reading work chats, trying to extract important information from a flood of messages. After implementing eight AI agents, the same work is now completed in 30 minutes, freeing up management from routine tasks to focus on strategic objectives.

Manual chaos, lost tasks, endless approvals, and errors are a familiar picture for many companies. In a distributed structure with dozens of employees and multiple legal entities, this multiplies exponentially. Every lost document, every unanswered question, every missed candidate response represents direct losses of time and money. Today, this pain can be addressed, and it doesn't require a complete overhaul of all processes.

Operational Chaos: How Routine Consumed Time and Resources

Before implementing AI agents, "Pizza Surgut," like many growing companies, faced increasing operational chaos. The distributed structure with multiple legal entities and a constant flow of employees exacerbated the problem. Routine tasks didn't just consume time; they created bottlenecks where tasks were lost and errors accumulated.

• Document Management. Up to 200 accounting and legal documents had to be processed manually daily. This process involved opening each file, manually entering information, renaming, and filing them. This took 6-7 hours a day, equivalent to a full workday for one employee solely dedicated to this mechanical task.
• Recruiting. Reviewing up to 100 applications daily from various platforms, such as Telegram and the company website, took several hours. Transferring candidate profiles from Telegram and the website into structured tables was entirely manual, leading to delays and potential errors.
• Communications. Managers spent an enormous amount of time reading work chats on Telegram. Amidst hundreds of messages, important tasks and critical information were easily lost. Additionally, employees constantly asked repetitive questions, distracting administrators and managers from more important matters.
• Financial Control. Daily reconciliation of revenue between online cash registers and bank statements required manual checks and comparisons, which was prone to errors and slowed down the daily closing process.

The Path to AI Agents: A Comprehensive Solution for a Distributed Network

The company realized that piecemeal automation would not fully solve the problem. A systemic approach was needed, capable of integrating various aspects of operational activity. Existing IT solutions often required rigid process formalization or were too cumbersome for rapid implementation. "Pizza Surgut" sought a flexible tool that could take on routine, yet critically important tasks, operating autonomously and minimizing human intervention.

The choice fell on AI agents, capable of not just executing scripted actions, but adapting to data flows, understanding context, and making decisions within defined rules. This allowed for the creation of an entire ecosystem of eight specialized agents, each responsible for its own area of work.

How AI Agents Were Designed: Eight Modules for Eight Tasks

To address the complex set of problems, eight independent yet interconnected AI agents were designed. Each was tailored to a specific task, ensuring maximum efficiency and accuracy. The logic of each agent's operation was built on principles of autonomy, integration with existing systems, and minimization of human involvement.

• Document Management AI Agent. This agent was developed to automate the processing of incoming financial and legal documents. It constantly monitors for new files in cloud storage, automatically standardizes their format, performs Optical Character Recognition (OCR), classifies documents by type (UDF, invoices, acts), extracts key details, and renames files according to internal standards, filing them into appropriate archive folders.
• Resume AI Chatbot. The agent's goal is to automate the initial screening of candidate applications. It analyzes messages in Telegram chats, recognizes candidate profiles, extracts necessary information (full name, contacts, experience), and forms structured rows that are automatically entered into a general candidate table.
• Chat Summarization AI Agent. This agent daily collects messages from work Telegram chats. Using natural language processing algorithms, it filters out "chatter" and irrelevant information, forming a structured summary of key events and tasks, which is then sent to managers.
• Employee Auto-Reply AI Bot. The bot analyzes employee questions in corporate chats, matches them with a knowledge base (editable in Google Sheets), and automatically generates a relevant response, attaching links to necessary documents or instructions.
• Recruitment Automation AI System. This agent is integrated with popular job search platforms (hh.ru, Avito) via API. It automatically retrieves applications, extracts candidate data, saves them into a unified table without duplicates, and, using defined rules, filters the most relevant candidates.
• Revenue Reconciliation AI System. The agent automatically retrieves data from the online cash register system ("Kontur OFD") and various banking systems (Sberbank, VTB, T-Bank, Alfa-Bank). It reconciles data from different sources, identifies discrepancies (e.g., receipts without corresponding deposits or vice versa), and generates a detailed report in Google Sheets.
• First-Line Tech Support AI Agent. A Telegram bot receives inquiries from employees, searches for answers in the knowledge base. If no relevant answer is found, the agent routes the request to the Service Desk or a specialized chat, recording user data in the process.
• Legal Change Monitoring AI Agent. Weekly, this agent reviews official sources, such as government agency and regulator websites. It filters materials by industry criteria, forms a legally significant digest, and publishes it in the corporate Telegram channel, adding data from the Central Bank and CPI.

Implementation: From Pilot to Full Transformation

The implementation of AI agents proceeded in stages, starting with the most critical and resource-intensive processes where the impact would be most noticeable and easily measurable. The document management and chat summarization agents were launched first, as these areas consumed the most management time.

The company actively involved employees in the process, demonstrating the benefits of automation. Training sessions were conducted to explain how the agents worked and their role in optimizing daily tasks. This helped overcome initial resistance and contributed to the rapid adoption of new tools. Gradually, as systems were refined and efficiency was proven, other agents were brought online, covering new areas from recruiting and financial control to tech support and legislative monitoring. The entire implementation process took several months, ensuring a smooth transition and minimizing stress for the team.

Results: Time Savings and Increased Transparency

The implementation of AI agents brought "Pizza Surgut" not only time savings but also a qualitative improvement in operational activities:

• Routine Reduction. The most visible result is that manual document processing, which previously took 6-7 hours, is now performed by an AI agent in 30 minutes. This freed up valuable human resources.
• Manager Time Savings. Chat summarization allowed managers to receive concentrated digests instead of having to review hundreds of messages, freeing up their time for strategic tasks.
• Accelerated Recruiting. Automated processing of applications allowed for finding and filtering relevant candidates according to specified criteria in minutes, significantly speeding up the hiring process.
• Reduced Administrator Workload. The auto-reply bot for employees significantly reduced the flow of repetitive questions, easing the burden on administrative staff.
• Increased Financial Transparency. Automated revenue reconciliation eliminated the risks of manual errors, ensuring complete transparency and accuracy of financial data.
• Optimized Tech Support. First-line support, handled by a bot, accelerated response times for users and relieved the support team.
• Up-to-Date Information. The legal change monitoring agent ensures timely receipt of critical updates without manual searching, minimizing risks.

How to Implement This in Your Business: Step-by-Step Towards Digital Transformation

The "Pizza Surgut" case demonstrates that comprehensive automation with AI agents is accessible not only to large corporations. If your business faces similar problems of routine and operational chaos, here's where you can start:

• Identify the most resource-intensive routine tasks. Begin with areas where employees spend the most time on repetitive actions: document management, initial request processing, data collection.
• Pinpoint information loss points. Where do tasks get lost, and important messages go unnoticed? This is an ideal place to implement a summarization or routing agent.
• Assess the load on support and HR. If employees ask many repetitive questions, or recruiters are overwhelmed with applications, an AI bot can significantly reduce this burden.
• Start small, scale gradually. Don't try to automate everything at once. Choose one or two processes with clear, measurable results, refine them, and then gradually expand functionality.
• Integrate AI agents into existing tools. The less employees have to change their habits and learn new platforms, the faster the adaptation will be, and the higher the efficiency.

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