At the NVIDIA GTC event in San Jose, deepset introduced its Custom AI Agent Solution Architecture, designed for businesses to deploy AI agents in both cloud and on-premises settings. This innovative solution combines deepset’s orchestration capabilities with the Haystack open-source framework and NVIDIA AI Enterprise software. It aims to help organizations build and manage AI agents while ensuring data security and control over AI processes. The architecture includes high-performance tools like the Triton Inference Server and NVIDIA NeMo, supporting enterprise-level security and compliance. CEO Milos Rusic highlighted the importance of trust and adaptability in AI solutions, while NVIDIA’s Amanda Saunders emphasized the necessity of robust orchestration and governance for effective enterprise AI deployment.
Deepset Launches New AI Agent Solution at NVIDIA GTC Event
At the recent NVIDIA GTC event held in San Jose, California, deepset unveiled its innovative Custom AI Agent Solution Architecture. This new offering is designed to help businesses effectively deploy AI agents in both cloud and on-premises settings, enhancing the way organizations manage their artificial intelligence workflows.
Key Features of the Custom AI Agent Solution
Deepset’s solution merges its advanced large language model orchestration capabilities with the Haystack open-source framework and NVIDIA AI Enterprise software. This powerful combination allows companies to create and oversee AI agents while ensuring their data remains secure and they maintain control over operations.
The architecture supports enterprise-grade security and compliance through several features, including:
– Optimized performance via NVIDIA’s Triton Inference Server
– NVIDIA NIM microservices for advanced text embedding and reranking
– Robust governance and orchestration capabilities
Quotes from Company Leaders
Milos Rusic, the CEO of deepset, emphasized the importance of trust and security in AI solutions. He stated, “Enterprises need AI solutions that don’t just process information but do so with trust, security, and adaptability.” He added that the integration with NVIDIA AI Enterprise software allows businesses to have full oversight of their AI workflows, whether they operate in cloud environments or on their own infrastructure.
NVIDIA’s director of generative AI software, Amanda Saunders, also shared insights on AI deployment. She noted, “Enterprise AI needs more than just models; it requires robust orchestration, infrastructure, and governance.” Saunders highlighted how the partnership with deepset enables businesses to deploy optimized AI agents effectively.
Conclusion
The new Custom AI Agent Solution Architecture from deepset represents an exciting advancement in AI technology. By combining powerful orchestration tools with NVIDIA’s infrastructure, organizations can enhance their operational capabilities while ensuring security and control.
Tags: AI Solutions, Deepset, NVIDIA GTC, Custom AI Agent, Cloud Deployment, Data Security, Business Technology, AI Workflow Management, Artificial Intelligence
What is the Custom AI Agent Solution from Deepset?
Deepset’s Custom AI Agent Solution lets businesses create tailored AI assistants that can understand and respond to specific queries. It can help companies provide better customer support and improve user interactions.
How can I customize my AI agent?
You can customize your AI agent based on your unique needs. This includes training the AI on your own data, setting up specific rules and responses, and modifying its personality to fit your brand.
What industries can benefit from using Deepset’s AI agents?
Businesses in various industries can benefit, such as retail, healthcare, finance, and education. The flexibility of the AI makes it useful for any field that needs responsive, intelligent interaction.
Is it easy to set up Deepset’s Custom AI Agent?
Yes, Deepset has designed the setup process to be user-friendly. You don’t need to be a tech expert. There are guides available to help you through each step of creating and managing your AI agent.
How can I measure the success of my AI agent?
You can track the AI agent’s performance by looking at metrics like response time, user satisfaction, and the number of successful interactions. Regularly reviewing these metrics will help ensure your AI continues to meet your goals.
