Agentic AI

Agentic AI has applications in a variety of fields, including robotics, autonomous vehicles, virtual assistants, and decision-support systems. These AI agents can navigate complex environments, make informed choices, and adapt their behavior to achieve specific objectives.

In the field of robotics, agentic AI can enable robots to autonomously plan and execute tasks, adapting to unpredictable situations and making decisions to accomplish their goals.

Agentic AI can also be used in self-driving cars to navigate roads, respond to changing conditions, and make decisions to ensure safe transportation.

Similarly, agentic AI-powered virtual assistants can understand user needs, set their own goals, and take actions to provide personalized and effective support.

Regarding decision-support systems, agentic AI can analyze large datasets, identify patterns, and recommend optimal courses of action. This can be particularly useful in fields like finance, healthcare, and business strategy, where complex decisions must be made based on numerous factors. By leveraging their autonomous decision-making capabilities, agentic AI systems can assist human experts in making more informed and efficient decisions.

Some examples of existing agentic AI platforms include Anthropic's Claude, OpenAI's GPT-3, and DeepMind's AlphaGo. These systems demonstrate autonomous decision-making, goal-setting, and adaptability within their respective domains. We can build agentic AI based on those platforms, and combine it with another so it will create a systematic workflow that fulfill the needs of the clients and users.