How to Deploy AI Chatbots for HR

If you search the Internet for AI chatbots, you're likely to repeatedly see the terms AI Factory and Agentic AI. The term AI Factory is relatively new and the associated marketing largely speaks of filling entire datacentres with the latest rack-scale GPU-accelerated infrastructure - you can learn more by reading our What is an AI Factory blog post. Whilst this is true of where multi-national organisations may ultimately take their AI infrastructure, it misses the point that an NVIDIA-certified AI factory reference architecture starts as small as just four nodes.

That's it - just four nodes, connected via low-latency networking to high performance storage, and you have a state-of-the-art AI factory for delivering innovation such as an interactive retrieval-augmented generation (RAG) HR chatbot agent, capable of autonomously making decisions, planning, and acting to achieve goals with minimal human intervention (agentic AI).

An AI factory of this type is required, as building an HR agent accurate and responsive enough to be useful, presents an enormous technical challenge. This is because agentic AI uses sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems. To achieve this and depending on the required chatbot features, it may be necessary to extract insights and generate new content from diverse in-house data sources, including text, images, videos, audio, animations, and even 3D models. On top of this is the challenge to deliver immediate and natural-sounding responses, even in the presence of background noise, poor sound quality, and diverse dialects and accents. The AI factory infrastructure provides a platform powered by NVIDIA inference microservices (NIMs) such as Riva, ACE, Audio2Face and Omniverse, that work on an avatar's attributes, its speech and translation - if needed - to deliver real-time relevant responses.

Alongside these obvious advantages in developing such a complex model, the AI factory infrastructure also offers several key business benefits:

• Accelerated time to market: an NVIDIA-certified structured approach using recommended designs means your organisation can deploy AI solutions faster, reducing the time to achieve business value
• Performance: an AI factory solution is built upon tested and validated technologies and incorporates design best practices, AI workloads will run at peak performance, maximising ROI
• Reduced complexity: embracing pre-defined technologies shortens deployment timelines, avoiding design and planning pitfalls
• Security: the AI factory infrastructure is engineered with zero trust in mind, supporting confidential computing and optimised for the latest cybersecurity AI standards, keeping your sensitive data secure

Starting your chatbot agent project with a four-node AI factory infrastructure from Scan will give your organisation the foundation to reap the benefits - realising efficiencies, generating cost savings and perhaps most crucially, gaining and maintaining competitive edge. Furthermore, as the AI factory infrastructure is modular, being made up of server nodes, network and storage devices, it can be simply scaled-up as your virtual HR agent roll-out expands, or if your AI projects diversify into deploying intelligent robots within your organisation.