Deroni Uses ABI to Turn AI from a Tool into an Integrated Part of the Business
Key outcome
AI integrated into Deroni's real business environment
Context
Deroni implemented ABI as part of its real business environment. After a several-day process of understanding the company's systems, data, processes, and structure, ABI built a working context for the way the business operates. This allowed ABI to start creating practical value from the very beginning — analysing the real business situation, recommending actions, executing specific tasks, and gradually expanding the company's AI capabilities according to Deroni's priorities.
The Problem
This implementation demonstrates the core idea behind ABI: AI should not be a separate tool that the business has to learn how to use. AI should become an integrated part of the business — connected to its data, processes, systems, people, and real priorities.
A business with real complexity
Deroni is one of the leaders in the food and beverage industry in Bulgaria — a brand with a long-standing history and a complex business model that brings together agriculture, production, quality control, logistics, commercial operations, management, and daily operational decision-making.
The company has developed an end-to-end production cycle — from its own agricultural resources in the “Gardens of Deroni” to processing, quality control, and the market realisation of its products. The gardens are located in the Upper Thracian Plain across 3.15 million square metres, where millions of vegetable plants are planted every year. During the active season, Deroni harvests 60–70 tons of ripe vegetables per day, which are processed within hours in the company's production facilities.
Behind this model stands a strong production infrastructure: three production plants, 14 technological lines, robotic processes, modern laboratories for continuous control, and certified production practices. The first factory in Stara Zagora was established in 1996, and the factory in Haskovo in 1999, highlighting the company's long-standing experience in building and managing a large-scale production environment.
This is exactly the type of business environment where AI creates the greatest value. At this scale, and with this level of connectivity between agriculture, production, logistics, trade, control, and management, it is not enough to add a separate chatbot, BI tool, or predefined AI agent. To be useful, AI must work with the company's specific processes, understand the relationships between different parts of the business, and be able to execute tasks according to the real needs of the teams.
AI that adapts to the business
Many companies begin their AI journey through separate tools — one for analytics, another for documents, a third for automation, and a fourth for communication. This can be useful at the beginning, but it often leads to fragmentation. AI remains outside the real business context and becomes yet another tool that people need to manage.
ABI takes a different approach. The goal is not for the client to adapt to predefined AI functions. The goal is for AI to adapt to the client.
At Deroni, the implementation began by building a working business context. ABI gained access to the relevant systems and data, went through a process of understanding the company's structure, processes, business logic, and way of working, and began to understand what matters to the different teams.
This initial stage was key. Instead of starting as an isolated AI interface, the platform began building a connection with the real environment in which the business works every day.
From implementation to real work in a matter of days
The implementation process followed several consecutive stages.
First, ABI gained access to Deroni's relevant systems and data sources. This allowed the platform to work not with abstract information, but with the company's real context.
Then ABI went through business-context onboarding — a process of understanding how Deroni works. ABI understood the company's structure, processes, data, dependencies, decision-making logic, and operational priorities. Even during this process, ABI began creating the first practical results, which became useful to the business from the very beginning of actual use.
After the initial period, Deroni can now independently assign tasks to ABI. This is the essential difference. The platform does not simply provide ready-made functions. It allows the client to define what is needed, when it is needed, and how it should be implemented.
From this point forward, ABI helps Deroni independently adapt AI in different directions according to its current priorities.
What ABI Does in Deroni's Real Business Environment
ABI understands
It builds context for the company's systems, processes, structure, and business logic.
ABI analyses
It works with data, identifies dependencies, summarises information, and produces business insights that support different teams and management decisions.
ABI recommends
It does not stop at describing the situation. It can offer interpretation, possible next actions, and directions for improvement.
ABI communicates in business language
Teams can interact with the platform naturally, without translating every need into a technical request or complex specification.
ABI executes
Within the defined context, access, permissions, and business rules, the platform takes on specific tasks and returns a completed result.
ABI builds
One of its most important capabilities is the ability to expand the business environment with new functionalities. The client does not choose from a limited menu of prebuilt AI functions. Deroni independently defines what to assign to ABI and in which direction to develop its AI capabilities.
What this project shows about ABI
The implementation at Deroni is an important example of how we at Neural Brothers see the future of AI for business.
The next phase of AI adoption in business will not simply be the choice of “one more” tool. Companies need an AI platform that understands their business, processes, priorities, systems, and data, communicates with teams, and evolves according to the company's real needs.
ABI was created exactly for this. It does not start from a predefined list of functions. It starts from the client's business.
“With ABI, we were able to approach AI through the real needs of the business, rather than through a predefined set of functions. This was important for us because Deroni has a complex environment, with different processes, systems, teams, and daily decisions that need to be understood in context.”
“After the initial process of understanding our systems, data, and processes, ABI began executing specific tasks, providing recommendations, and developing new functionalities according to our priorities. This is a valuable approach because it gives us the freedom to decide how AI should evolve within the company and how it should support the business where it can create the greatest value.”
Nikolay Kolev
Manager Distribution and Logistics at Deroni Ltd.
“For us, the implementation of ABI at Deroni is an important example of how AI can be introduced into a real business environment without starting from a predefined tool or fixed scenario. Deroni is a company with scale, complex processes, and different operational levels, which makes the project especially valuable for us.”
“It is precisely in this type of environment that the strength of ABI becomes visible — its ability to enter the context of the business, work with its systems and data, and gradually become a platform through which the client develops its own AI capabilities. This is the direction in which we believe practical AI implementation in business will evolve.”
Milen Nedev
Co-founder, Neural Brothers
Reference available upon request. Some details have been generalized to protect client confidentiality.
Facing a similar challenge?
We'd be happy to discuss how we might approach your specific situation. Every engagement starts with understanding your unique context.
Let's Talk