Balyasny Asset Management (BAM) has collaborated with Google Cloud to deploy Gemini models into BAM’s proprietary AI research platforms.
The partnership will enable analysts to leverage Gemini’s specialised capabilities for quantitative work, including rapid analysis of large financial datasets, high-accuracy document retrieval and cost-effective performance.
BAM currently operates proprietary internal applications, such as BAMAgent, to streamline research workflows and orchestrate specialised AI models and agents across more than 80 internal databases and market feeds, which in turn can use Gemini to synthesise financial research, earnings transcripts, and live market data.
Both firms have also confirmed that the new offering is integrated with Google Cloud’s secure infrastructure and Gemini’s strict data isolation, to ensure the asset manager’s proprietary trading data and strategies remain confined to the private cloud environment.
“Across our investment practice, different research tasks demand specialised model capabilities,” said Charlie Flanagan, chief AI officer at Balyasny Asset Management.
“When our research agents evaluate thousands of market feeds simultaneously, model speed, retrieval accuracy, and cost efficiency are critical. Gemini delivers the throughput our analysts need for high-volume document search, as well as the multimodal reasoning required to analyse complex financial charts and corporate disclosures.”
Read more – Fireside Friday with… Balyasny Asset Management’s Charlie Flanagan
Both BAM’s applied AI team and Google Cloud are set to continue their collaboration over the coming months, with developments expected in early access programs and testing upcoming Gemini models to enhance AI performance.
Speaking to The TRADE in 2024, Flanagan explained that establishing and enhancing AI-focused education is key to successful implementation across the industry.
“If something is working really well in one team or one vertical within the firm it then becomes about translating that. It’s never a direct translation but taking the lessons about the AI technology that’s working well somewhere and then adopting it somewhere else allows us to achieve more scale within the firm.
“[…] At the end of the day, before trust comes education. It’s about helping folks understand where these models can add value right now and where they can’t.”