AI Assist, delivered via Xmon, has a natural language interface that gives users contextual answers about their reference data usage.
TRG Screen, a provider of market data and subscription cost management technology, has released Xmon AI Assist, a capability intended to bring conversational analytics to market data cost management, officials say.
Xmon is a reference data cost and usage monitoring solution that offers “visibility into consumption patterns, cost drivers and vendor billing,” officials add. The new capability is expected to deliver “deeper insight, faster analysis and proactive cost optimization” that will help financial services firms make “smarter, data-driven” decisions.
Built and tested via “extensive customer input,” the feature requires no onboarding and is available to all Xmon clients at no additional cost, officials say.
AI Assist, delivered via Xmon, has a natural language interface “that lets users ask questions about their data and get immediate, contextual answers,” officials say. “From identifying cost drivers and usage patterns to uncovering savings opportunities, it simplifies analytics and accelerates access to actionable insight.”
The capabilities are “a major step forward in TRG Screen’s mission to democratize access to insight, accelerate data-driven decisions, and give firms greater control over one of the industry’s most complex and expensive data categories,” officials say.
“Xmon AI Assist redefines how clients engage with their reference data cost transparency, optimization, and usage,” says Christophe Plouvier, Xmon product director at TRG Screen, in a prepared statement. “Instead of static dashboards or manual reports, users can simply ask questions — why costs changed, what’s driving usage or where saving opportunities can be found — and get instant answers.”
An anonymous customer says the new offering is a “game-changer.”
“We’ve been testing Xmon AI Assist within our reference data management workflows, and it’s been a game changer,” says a market data officer at a Tier 1 global bank. “By simplifying complex data interactions and enhancing transparency, it elevates operational efficiency and empowers teams to make smarter, faster decisions around reference data governance and spend.”
The new offering was developed via a Retrieval-Augmented Generation (RAG) framework, and “combines large language model reasoning with each client’s own Xmon analytics to deliver contextual, explainable and accurate responses while maintaining full data privacy. It empowers market data teams to uncover anomalies, trace cost drivers, explore usage patterns, and pinpoint optimization opportunities without relying on technical queries or data specialists,” officials say.
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