LSEG Integrates Tick History Data With Google Cloud’s Vertex AI
LSEG has announced that its cloud-based historical tick data is now accessible directly through Google Cloud’s largeQuery and Vertex AI platforms, marking a significant advance in the firm’s push to power financial services with scalable, enterprise-grade artificial intelligence. The integration enables banks, hedge funds, asset managers, and trading firms to run AI and machine learning workloads on LSEG’s deeply granular tick datasets without the friction of managing complex infrastructure or performing manual data ingestion.
Through Vertex AI, financial institutions gain the ability to interrogate decades of historical market data, combine it with internal datasets, and apply advanced AI models to uncover patterns, generate predictive insights, and enhance algorithmic decision-making. The collaboration fits directly into LSEG’s “LSEG Everywhere” strategy, which aims to deliver licensed, trusted data across cloud environments to accelerate adoption of AI in .
Tim Anderson, Head of Quantitative & Economic Data & Tick History at LSEG, described the milestone as a “significant leap forward,” noting that the combination of LSEG’s data with Google Cloud’s AI stack gives users unprecedented capability to process, query, and analyze historical tick-level information at scale. This shift, he said, gives institutions a quicker, cost-effective path to extracting meaningful insights from some of the most complex datasets in global finance.
Takeaway
Bringing AI, Natural Language, and largeQuery Performance to Tick-Level Analytics
The partnership offers several capabilities that materially elevate how financial institutions leverage . One of the most immediate benefits is the acceleration of processing speed: queries that previously required hours due to the sheer volume of tick-level feeds can now be executed in seconds on Google’s distributed compute architecture. This speed allows quants and data scientists to iterate quicker, test more hypotheses, and respond rapidly to market dynamics.
Vertex AI’s native support for natural language interfaces and transparent SQL outputs also broadens access beyond specialized engineering teams. Analysts, strategists, and risk managers can query datasets conversationally or through simple SQL, lowering the technical barrier to advanced analytics. At the identical time, largeQuery’s compute optimization and efficient scanning by eliminating the need for dedicated local compute clusters or on-premise AI hardware.
Google Cloud’s Director for FSI UK, Graham Drury, emphasized that this collaboration empowers institutions to perform deeply insightful and cost-effective analysis of critical market data, marking what he called “a new era of financial market intelligence.” By grounding AI agents in high-quality tick history, firms can adopt capable of contextual reasoning—beyond basic pattern recognition—using reliable, licensed historical datasets.
Takeaway
Scalable, Cost-Efficient AI Adoption for Firms of All Sizes
This integration is expected to be especially impactful for mid-sized and emerging financial institutions that lack the resources to maintain on-premise AI infrastructure. Through Google Cloud, firms can scale compute usage on demand, apply high-level AI models, and integrate proprietary data with LSEG tick feeds without heavy initial investment. This democratizes access to advanced data science capabilities that historically were concentrated among the largest global trading houses.
The collaboration also supports the adoption of agentic AI—systems that can make contextual decisions, reason across datasets, and perform tasks autonomously. By grounding these AI agents in structured, trusted market history, firms can deploy more reliable tools for portfolio construction, market surveillance, risk modeling, and liquidity forecasting. This reduces the time typically lost wrangling raw data, allowing teams to focus on strategy and insight generation.
The integration reflects a broader shift across capital markets: AI is transitioning from an experimental phase into a core operational component, and high-quality, licensed data is the foundation. With LSEG’s tick history now embedded directly into Vertex AI, financial institutions gain a turnkey environment for building AI-driven strategies, , and responding to market events with precision and speed.
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