RAG Framework

The RAG Framework allows RPA bots and AI LLM models to share data and insights effortlessly. This exchange is crucial for tasks that require a combination of rapid automated action (handled by RPA bots) and complex decision-making or problem-solving (handled by AI models).

The RAG Framework is designed to be scalable, accommodating an increasing number of bots and AI models as your business needs grow. It's also flexible, meaning it can be adapted to various business contexts and requirements.

By combining the efficiency and precision of RPA bots with the analytical capabilities of AI models, the RAG Framework ensures tasks are executed faster while simultaneously reducing the number of errors.

The framework is built with integration in mind, meaning it can easily fit into your existing technology infrastructure without the need for significant overhauls or complex setups.

Despite its advanced functionality, the RAG Framework features a user-friendly interface, making it accessible for teams with diverse technical skill levels, facilitating ease of use regardless of experience.

Recognizing that each business has unique needs, the RAG Framework is customizable. This means it can be tailored to meet the specific requirements of your business processes and objectives.

The AI models within the framework are capable of learning and improving over time. This means the more they interact with RPA bots, the better they become at providing relevant and effective solutions.

Security is a top priority in the RAG Framework, ensuring that all data exchanged between RPA bots and AI models is protected and handled in compliance with the highest industry standards.