Development of AI assistants that help users perform information, analytical, or operational tasks through natural-language interaction.
Assistants can combine language models with retrieval, tools, application APIs, structured data, and task-specific rules.
Examples include research assistants, technical assistants, documentation assistants, data assistants, and internal workflow interfaces.
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.