Selected engagement · Food production and distribution

AI-Powered Business Planning & Operational Intelligence

Kaya Development worked with Demkay Gıda to integrate artificial intelligence into its core planning and decision-making processes—helping management anticipate demand, plan production, manage distribution capacity, and understand sales-network performance.

ClientDemkay Food Production & Distribution Company
EngagementArtificial intelligence integration
Business contextProduction, distribution, and sales planning
FocusDemand forecasting, operational optimization, sales intelligence
Demkay Food Production & Distribution Company
Client collaboration

A decision-support layer built around the way the business operates.

Demkay Gıda operates both as a food producer and as a distributor of established consumer brands. Its planning environment therefore needs to connect demand, production, inventory, logistics, sales activity, and network performance.

We designed the AI integration around the company's existing operational data—not as a standalone technology, but as an intelligence layer that supports day-to-day decisions and longer-term business planning.

The challenge

Move from reactive operations to a more predictive planning model.

Food production and distribution businesses must continuously balance changing demand, inventory requirements, production capacity, logistics, and sales performance. Historical reports explain what happened, but often arrive too late to shape the next operational decision. The challenge was to create greater visibility into what the business may need next—across products, periods, sales channels, regions, and customer groups.

Our approach

We brought operational data together to support forward-looking decisions.

Kaya Development connected historical sales patterns, product demand, distribution activity, operational performance, and business-planning data within an AI-enabled decision environment. The system was structured to help management assess future demand, translate forecasts into production and inventory requirements, monitor the sales network, and identify changing customer or market patterns earlier.

What we delivered

An operational intelligence environment spanning demand, production, distribution, and sales.

01

Demand forecasting

Structured forward-looking analysis across products, periods, sales channels, and customer groups, including annual and seasonal demand patterns.

02

Production requirements planning

Connected expected demand with what may need to be produced, in what quantities, and at what point in time for Demkay Gıda's manufactured products.

03

Inventory and distribution optimization

Supported stock-requirement analysis and forward-looking distribution planning for both manufactured products and the consumer brands distributed by the company.

04

Sales intelligence

Enabled trend analysis across products, regions, territories, channels, and customer groups to reveal growth, decline, and changing demand.

05

Network and team performance

Created a clearer view of sales-network and employee performance, helping identify high-performing and underperforming areas earlier.

06

AI-assisted management reporting

Turned operational information into decision-ready analysis that helps management prioritize production, distribution, workforce, and sales resources.

Management intelligence

Business data became a basis for asking what is likely to happen next—and how the company should respond.

The intelligence layer supports questions such as what the business may need next month, which products could experience higher demand, where stock requirements may increase, which territories are growing or declining, and where production or distribution resources should be prioritized. This shifts reporting from retrospective explanation toward forward-looking management insight.

What the work demonstrates

AI creates enterprise value when it is connected to real operational decisions.

The result is an AI-enabled business-planning and operational-intelligence environment designed to make production, distribution, workforce, and sales decisions more predictable, coordinated, and data-driven. For organizations managing complex production and distribution networks, this approach can reduce uncertainty, improve resource planning, and give management greater visibility before critical decisions need to be made.

Integration principle. The AI layer supports management judgement by organizing evidence, surfacing patterns, and testing likely future requirements. Accountability for operational and commercial decisions remains with the business.

Turn operating data into a clearer view of what comes next.

Talk to us about demand forecasting, AI-enabled planning, operational intelligence, or distribution optimization.

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