LLMs in Companies: Why a Unified Semantic Core Is Needed
Mikhail T. (Sh0ny)
25 июня 20261 min read
In short
If employees use different LLMs, each chatbot builds its own version of the company’s meaning. Let’s explore why a common semantic framework is essential.
Companies are increasingly adopting LLMs, but they’re running into an unexpected problem: inconsistent meanings. When employees use ChatGPT, DeepSeek, or corporate chat platforms, each conversation creates its own interpretation of terms.
What’s the risk?
The word “batch” can mean:
- a batch of materials in the warehouse;
- a production batch;
- a batch for quality control;
- a product series;
- a traceability object;
- an analytical breakdown of cost of goods sold.
The model infers meaning from context, but without a unified corporate framework, discrepancies arise. This is tolerable in correspondence, but in ERP projects, QMS, management accounting, and manufacturing—it’s critical.
What Is Proposed?
The author of this article believes that a domain-specific semantic layer is needed—not just a set of prompts, but a common semantic framework for the enterprise. Such an approach will become one of the most practical artifacts during LLM implementation.
Conclusion
Without a unified semantic core, every interaction with an LLM risks leading to misinterpretations, which would negate the benefits of speed. Establishing context is a step toward reliable automation.
Source: Habr