Development of AI systems that can plan tasks, use tools, interact with software, and execute multi-step processes.
Agentic systems may combine language models, tools, APIs, memory, planning logic, validation steps, and controlled execution environments.
Applications include research agents, software assistants, data-processing agents, information gathering, and multi-step technical workflows.
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.