As Nvidia releases its NeMo microservices to embed AI agents into enterprise workflows, research has found that almost half of businesses are seeing only minor gains from their investments in AI.
NeMo microservices are a set of tools, some already available, which developers can use to build AI agents capable of integrating with existing applications and services to automate tasks, and manage the lifecycle of agents to keep them updated as necessary with the latest information.
"There are over a billion knowledge workers across many industries, geographies, and locations, and our view is that digital employees or AI agents will be able to help enterprises get more work done in this variety of domains and scenarios," said Joey Conway, Nvidia's senior director of generative AI software for enterprise.
NeMo microservices are also included in the overarching Nvidia AI Enterprise suite of developer tools.
The components include NeMo Curator for gathering enterprise data, which gets passed to NeMo customizer, described by Conway as a microservice that "takes the latest state-of-the-art training techniques and teaches models new skills and new knowledge so we can ensure that the models powering the agents stay up to date."
NeMo Evaluator is intended to check that the model powering the agent actually has improved instead of regressing, while NeMo Guardrails try to keep the agent on topic so it operates as intended and avoids safety and security pitfalls.
Nvidia envisions these microservices working in a circular pipeline, taking new data and user feedback, using this to improve the AI model, then redeploying it. Nvidia refers to this as a "data flywheel," although we can't help feeling that this misunderstands what an actual flywheel does.
Visualization of this 'data flywheel' complete with creepy Jensen Huang avatar in center – click to enlarge
Conway described NeMo microservices as "essentially like a Docker container." The orchestration relies on Kubernetes, with additional features such as Kubernetes Operators to help.
"We have some software today to help with the data preparation and curation. There will be a lot more coming there," he said.
Nvidia claims broad software support for its new AI toolkit, including enterprise platforms such as SAP, ServiceNow, and Amdocs; AI software stacks like DataRobot and Dataiku; plus other tools such as DataStax and Cloudera. It also supports models from Google, Meta, Microsoft, Mistral AI, and Nvidia itself.
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Examples where NeMo microservices are already being put to work include Amdocs, which is laboring on three types of agents for its telecoms operator customers, Nvidia said.
These comprise a billing agent, a sales agent, and a network agent. The billing agent focuses on query resolution, while the sales agent works on personalized offers and customer engagement as part of deal closure. The network agent will analyze logs and network information across geographic regions and countries to proactively identify service issues.
Developers can download NeMo microservices from the Nvidia NGC catalog, or deploy it as part of Nvidia AI Enterprise suite.
Also being released today is research published in the UK which claims that businesses are spendingan average of £321,000 ($427,000) on AI in a bid to improve customer experience, though many are yet to see significant gains. It found 44 percent of business leaders indicated that AI has, so far, only delivered a slight improvement.
Despite this, nearly all respondents (93 percent) claimed their AI investment has delivered a good return on investment (ROI).
The research was commissioned by Storyblok, provider of CMS software for marketers and developers, which said that businesses need to look beyond surface-level implementations and integrate AI in a way that drives meaningful transformation.
It found the most popular use cases for AI among UK business leaders are website content creation, customer service, marketing analysis, translation services, and marketing content creation. ®
