Sberbank reduced business process analysis time by 4x: How an AI agent transformed Process Mining

Sberbank analysts used to spend tens of hours manually analyzing business processes, sifting through vast amounts of data. Now, with the implementation of an AI agent for their Process Mining platform, analysis time has been cut by four times. The agent autonomously processes up to a hundred million events per month, formulates hypotheses, and provides ready-made recommendations.

In a large company like a bank, business processes involve hundreds of millions of transactions and events that require constant analysis. Manual analysis of such data volumes means colossal labor costs, the risk of human error, and missed opportunities due to slow reaction times. Every hour spent on routine tasks is lost money and time that could be invested in strategic decisions. But this way of working is no longer necessary; this problem can now be solved.

The pain of manual analysis: why Process Mining wasn't reaching its full potential

Process Mining, or process analytics, allows for the visualization and analysis of business processes based on data from information systems. It's a powerful tool for identifying bottlenecks, inefficiencies, and deviations in operations. However, given Sberbank's scale, dealing with hundreds of millions of events per month, even specialized platforms still required significant manual effort.

Analysts had to manually extract data, build models, formulate hypotheses, test them, and interpret results. This was a labor-intensive and lengthy process that limited the frequency and depth of analysis. Often, by the time an analyst prepared a report, the situation had already changed, making the conclusions less relevant. The main problem was that the analysis process itself, despite the platform, remained largely manual and required deep involvement from specialists at every stage.

From routine to intelligence: why an AI agent became the next step

Existing Process Mining tools excelled at visualization and basic analysis, but they couldn't independently search for non-obvious correlations, generate hypotheses, or formulate ready-made recommendations. This all remained the responsibility of humans.

Sberbank faced the need not just to automate data collection, but to intellectualize the analysis process itself. An tool was needed that could not only display data but also "think," suggest solutions by testing dozens of scenarios without human intervention. This is why the company arrived at the idea of an AI agent that could take over the full analysis cycle, from data collection to generating a report with recommendations.

How the AI agent for Process Mining was designed

The AI agent was conceived as an intelligent assistant capable of performing a full cycle of process analytics. Its main task was not to replace specialists but to free them from the routine yet complex work of data searching and processing. The agent needed to possess the following key capabilities:

• Automated data collection and processing. Ability to interact with various data sources and process up to 100 million events per month.
• Hypothesis generation. Independent search for non-obvious problems and bottlenecks in processes, generating hypotheses about the causes of inefficiency.
• Hypothesis testing. Automated testing of dozens of hypotheses without human intervention, identifying root causes of problems.
• Report and recommendation generation. Preparing a complete report with conclusions, substantiated recommendations, and proposals for process optimization.
• Natural language interface. Ability to formulate tasks in natural language, without requiring deep knowledge of Process Mining methodology.

Thus, the agent was designed to become not just a tool, but a full-fledged partner for the analyst, capable of taking on the most labor-intensive and repetitive stages of work.

Implementation and integration into Sberbank's ecosystem

In 2025, the AI agent was launched within Sberbank. Implementation occurred in stages, starting with the most critical and high-volume processes where the impact of faster analysis would be maximal. A key aspect was training employees to interact with the agent. The emphasis was on the fact that the AI agent is not a replacement but a tool that allows the analyst to focus on intellectual work: interpreting findings, verifying causes, and making management decisions.

The integration of the AI agent into the existing Process Mining platform was seamless. Users did not need to learn new complex interfaces or special skills. It was sufficient to upload data and formulate the task in natural language, and the agent took on all the remaining work.

Results of Process Mining transformation at Sberbank

The main result of the implementation is not just time reduction, but a fundamental change in the analyst's role. Now, they don't spend tens of hours on routine data verification but receive ready-made insights for effective and accurate decisions in minutes. This accelerates the entire work cycle: from research to implementing changes. Furthermore, analysis can now be performed at any frequency and time, significantly increasing the responsiveness to changes in business processes.

How to implement this in your company: intellectualizing process analytics

Sberbank's case demonstrates that Process Mining can be much more effective if the routine part of the analysis is entrusted to an AI agent. If your company faces large data volumes and a need for deep process analysis, consider the following steps:

• Identify the most labor-intensive stages of process analytics. Where do your analysts spend most of their time on manual data collection, hypothesis testing, or report generation? These are ideal candidates for AI agent automation.
• Focus on hypothesis generation and recommendations. If your current platform only visualizes data, and "insights" still depend on human experience, an AI agent can take on this intellectual part, offering substantiated solutions.
• Ensure seamless integration. The easier it is for employees to interact with the AI agent (e.g., through natural language), the faster the adoption will be, and the higher the return on investment.

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