Awards & Events June 19, 2025
Alkymi is a finalist for the Data Management Insight Awards USA 2025
We are thrilled to announce that Alkymi has been shortlisted for the 4th Annual Data Management Insight Awards USA 2025! This recognition is a true honor, reflecting our ongoing commitment to transforming how financial institutions manage data. Being named among the best in the data management industry is a testament to our team's dedication to innovation and excellence.
Our Nominations:
Alkymi has been recognized in four categories for the 2025 Data Management Insight Awards USA:
🏆 Best Data Management Solution for Unstructured Data
🏆 Best AI-Based Data Management Capability
🏆 Best Buy-Side Data Management Platform
🏆 Most Innovative North American Data Management Provider
The Data Management Insight Awards shortlist is the result of careful review by an expert editorial team and an independent advisory board, who evaluate submissions based on their impact on capital markets, their relevance to the award categories, and the potential interest within the Data Management Insight community.
These nominations highlight Alkymi’s continuous efforts to empower financial firms with AI-powered automation solutions that help them scale operations, eliminate manual work, and unlock actionable insights from unstructured data.
Vote for Alkymi at the Data Management Insight Awards USA 2025!
The Data Management Insight Awards are recognized as a prestigious awards in the data management space, and your support can help us showcase the incredible work we’ve done.
Voting deadline: Friday, July 11, 2025, at 5 PM (UK time)
Please take a moment to vote, and thank you for helping us continue our journey towards transforming financial data management!
Alkymi wins Best Alternative Data Initiative & Best Private Markets Data Initiative at the 2025 IMD/IRD Awards by WatersTechnology.
Strategic Investment Group hosted Alkymi's CEO, as a guest speaker, for an AI summit for the firm's leadership team
Decoding ML and LLMs for financial firms: understand when to use each, their strengths, limitations, and how a hybrid approach can enhance data workflows.