By utilising the NayaOne Digital Sandbox and NVIDIA's accelerated computing platform, including NVIDIA NIM microservices, a part of the NVIDIA Ai Enterprise software tool, NayaOne aims to work towards further scaling the adoption of GenAI in financial services. Through this, the company aims to allow enterprises to accelerate the testing, development, and deployment of GenAI solutions, increasing time to value and time to market in sectors such as fraud, customer experience, and business efficiency use cases.
The current news comes after Smart Data Foundry and NayaOne teamed up to assist in the digital transformation of the financial services sector. The partnership was set to see Smart Data Foundry's aizle synthetic data sets integrated into NayaOne's Digital Sandbox, providing opportunities for accessing data within a secure environment.
Recently, GenAi emerged as a significant capability for financial services, allowing enterprises to analyse large data sets, generate synthetic data for risk-free experimentation, and improve decision-making features. By integrating NVIDIA AI Enterprise and NVIDIA NIM microservices into the NayaOne Digital Sandbox, the two companies intend to support enterprises in experimenting with AI models at scale, minimising time to market with risk-free experimentation.
When commenting on the announcement, representatives from NayaOne mentioned that their company saw an increased demand for AI-powered solutions and the partnership with NVIDIA is set to enable institutions to benefit from the capabilities of GenAI in a controlled and secure environment. In addition, NayaOne and NVIDIA plan to work on developing an ecosystem where financial institutions can prototype more efficiently, which in turn centres around leading to business advancement and growth initiatives.
As of the current news, enterprises can test new AI solutions in NayaOne's Digital Sandbox with NVIDIA's software and hardware tools, with them being able to experiment with NVIDIA NIM Microservices on-premise and with their cloud service provider. Through this, they can minimise integration risks. At the same time, financial institutions can conduct multiple proofs-of-concept simultaneously, leveraging their data and evaluating the efficacy of AI services before deploying.