As retailers increasingly rely on data to guide operations, many organizations are searching for faster ways to turn complex analytics into practical business decisions. Retail intelligence provider 11Ants has introduced Ant AI Retail Expert, a new tool designed to help retail teams quickly analyze data and make evidence based decisions across merchandising, marketing, and store operations.
11Ants, whose AI powered retail intelligence platform supports retailers operating more than 4,000 stores across eight countries, announced the launch of Ant, an artificial intelligence assistant built specifically for grocery and retail environments. The system enables business users to ask operational questions in plain language and receive immediate insights based on company data.
The release reflects a growing shift in retail analytics from traditional reporting systems toward conversational AI tools that provide faster decision support. Instead of navigating dashboards or manually compiling reports, employees can begin with a specific problem and receive contextual analysis along with recommended actions.
“For years, retail decision-making meant pulling reports and navigating dashboards to piece together an answer,” said Tom Fuyala, CEO of 11Ants. “Ant flips that model. You start with the problem you’re trying to solve, and it brings back the evidence, context and actions while those actions will still have impact.”
The Ant AI Retail Expert operates on top of 11Ants’ existing Retail Intelligence platform, which integrates data from multiple business systems including loyalty programs, point of sale systems, inventory databases, and budgeting tools. By consolidating these datasets into a unified cloud environment, the platform enables Ant to provide insights across customer behavior, product performance, and store level operations.
Rather than simply retrieving historical metrics, the system is designed to interpret patterns in retail data and explain why certain outcomes are occurring. It can highlight potential drivers of performance changes, compare scenarios, and recommend possible actions based on the analysis.
Retail teams can use the system to explore a wide range of operational questions, from understanding category performance trends to identifying customer purchasing patterns or diagnosing issues affecting individual store locations. The goal is to enable faster decision making while reducing reliance on specialized data analysts.
The platform is already being used by grocery retailer Farro Fresh, where executives say the technology has helped streamline internal decision making processes. By enabling teams across departments to access insights directly, the system reduces the time previously required to gather and interpret data.
“Using Ant has fundamentally changed how I start conversations in the business,” said Garth Sutherland, CEO of Farro Fresh. “Instead of asking what data we need, we’re asking what problem we’re trying to solve — for customers, for the team, and for the business. That shift alone has been transformational.”
Sutherland noted that tasks that previously required days of analysis can now be completed in minutes. Teams in marketing, merchandising, and operations are able to review insights during meetings rather than waiting for reports to be compiled.
“It’s not just giving us answers, it provides context, highlights likely drivers and suggests what to do next,” said Sutherland. “That’s a step change from data retrieval to true decision support. Our trading meetings are faster, richer and far more evidence led.”
According to 11Ants, Ant AI Retail Expert is designed to be deployed quickly within existing retail data environments without requiring organizations to build complex internal AI infrastructure or hire specialized data science teams.
As retailers continue to adopt AI driven analytics, tools that transform operational data into actionable insights may play an increasingly important role in enabling faster, evidence based decisions across store networks and supply chains.
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