Deployment of large language models as controlled inference services for applications, assistants, and internal systems.
Work may include model serving, quantization, inference configuration, API layers, resource management, and monitoring.
Deployments can support conversational systems, RAG, private assistants, research tools, and domain-specific language applications.
Implementation is selected according to the available data, technical constraints, required level of automation, and the existing software or research environment. The solution can be implemented as a standalone component or integrated into a larger system.
The resulting system is intended to provide a clear computational workflow that can be evaluated, maintained, and extended as the project develops. Model choice, data processing, interfaces, and deployment can therefore be adapted to the requirements of the specific project.