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ATOM AI- Powered Virtual Assistant (AVA)

Language Learning Models (LLMs), a subset of AI/ML models, excel in comprehending extensive human-readable data like guidebooks and tutorials intended to enhance human knowledge. These LLMs, combined with Generative AI, read such data and generate new artifacts based on their acquired knowledge. Recognizing the immense value of this technology in the Network Automation domain, Anuta Networks swiftly grasped the potential it holds for its end-to-end service orchestration and automation development platform, ATOM. With access to diverse network and IT artifacts, along with ATOM’s domain-specific and open-source knowledge, Anuta Networks initiated the integration of AVA. This virtual assistant empowers network developers to unlock unparalleled potential by harnessing the latest LLMs available, surpassing even their wildest imaginations for present and future networks.

Anuta ATOM AVA Components

Benefits of ATOM AVA

Enhanced Network Automation

ATOM AVA uses LLMs and Generative AI to process human-readable data, including guidebooks and tutorials, to gain a deep understanding of network configurations and policies, resulting in improved automation and reduced manual efforts.

Intelligent Guidance

ATOM AVA’s vast knowledge base enables it to offer thoughtful insights and recommendations, optimize configurations, identify performance bottlenecks, and provide proactive solutions for network efficiency.

Accelerated Use-Case Development

ATOM AVA’s integration with Anuta ATOM empowers developers to explore innovative use cases using LLMs and domain-specific knowledge, thereby accelerating development and maximizing value.

Streamlined Problem Solving

ATOM AVA’s AI capabilities analyze complex network data, rapidly pinpointing root causes and suggesting remedies for improved network reliability and customer satisfaction.

Realistic Interaction

ATOM AVA’s natural language processing allows user-friendly interactions, fostering better collaboration and understanding between users and the virtual assistant.

Network Resilience

ATOM AVA continuously learns from new data, staying up-to-date with network technologies, standards, and trends, ensuring customers’ networks remain competitive and resilient.

Components of ATOM AVA

1. Co-Pilot

Auto Code Generation (BPMN): This unique technology automates the generation of BPMN (Business Process Model and Notation) code, streamlining the creation of complex workflows. For instance, you can seamlessly generate BPMN code to integrate with platforms like ServiceNow, simplifying intricate integration processes.

Accelerates Workflow Development: The Co-Pilot significantly speeds up the development of workflows. This means that you can create, modify, and deploy workflows more efficiently, reducing development time and increasing overall productivity.

2. Doc Assistant

Knowledge Base: The Doc Assistant is equipped with a robust knowledge base, providing comprehensive documentation and resources. This is particularly useful for quicker onboarding of new team members, as they can easily access relevant information and guidelines.

Faster Onboarding: With the Knowledge Base at its core, the Doc Assistant streamlines the onboarding process. New team members can swiftly familiarize themselves with the platform’s functionalities and best practices.

3. Operator Assistant

Config & Compliance Management: The Operator Assistant simplifies configuration and compliance management tasks, minimizing the risk of errors and ensuring adherence to established standards.

Automates tasks and avoids errors: By automating various tasks, the Operator Assistant reduces the chances of human errors, leading to improved operational accuracy and consistency

4. Guided Troubleshooting

RCA Guiding Infrastructure: The Guided Troubleshooting feature offers a guided root cause analysis (RCA) infrastructure, helping you identify the underlying causes of issues more effectively.

Interactive Impact Analysis: This feature enables interactive analysis of the impact of different variables and factors, assisting in understanding the relationships between elements within your system.

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