Participated · Equity · Oct 2024

BMLL Technologies provides harmonised historical Level 3, 2 and 1 data and analytics across global equities, ETFs and futures, offering granular T+1 order book data and advanced pre- and post-trade analytics. Its customers include banks, brokers, asset managers, hedge funds, global exchange groups, academic institutions and regulators. The platform delivers immediate and flexible access to detailed market data for execution analysis, surveillance and market-structure research. Led by CEO Paul Humphrey and based in London, the company emphasizes use of the most granular order-book data to support algo development and validation. BMLL intends to use the new funding to expand operations and accelerate development efforts. BMLL Technologies supplies cloud-native, harmonized Level 3 historical order-book (T+1) data and analytics to banks, brokers, asset managers, hedge funds, and exchanges. Its platform captures every message with nanosecond-precision timestamps and applies normalization and harmonization processes to deliver high-quality, ready-to-query datasets. BMLL offers a cloud Data Science environment and web portal that removes the need for clients to buy, curate, and harmonize raw market data. The company’s data supports use cases including quant research, back-testing, transaction cost analysis, compliance, surveillance, and order-book simulation. Through a collaboration with FactSet, BMLL’s Level 3 capabilities are being surfaced as a Market-by-Price Level 2 tick-history product on a common delivery platform alongside FactSet’s Level 1 tick archive in Snowflake. BMLL was founded in 2014 in the machine-learning laboratories of the University of Cambridge.

Led · Series B · Jun 2024

Aidentified provides financial advisors, marketing teams, and other sales professionals with tools to identify, qualify, and convert new client relationships. Its platform combines professional and household data to offer a 360º view of clients and prospects. The company uses proprietary algorithms and relationship cloud functionality, empowered by AI and machine learning techniques. That relationship cloud is fed by 210 million consumer and 100 million professional U.S. profiles. Aidentified's platform delivers customer and prospect analytics, real-time wealth events, and nuanced relationship mapping. The company plans to use the funds to advance technological development and grow its team as client adoption accelerates. It raised $12.5m in Series B funding from FactSet. Aidentified builds AI-based relationship and sales intelligence that combines consumer and professional attributes into unified household profiles. Leveraging 210 million U.S. profiles, it uses AI and machine-learning technologies and proprietary Relationship Mapping algorithms to help customers search for prospects based on recent wealth events (stock trades, mergers and acquisitions, IPOs, management changes, new company investments), income, age, location, position, personal interests and more. The company was founded by twin brothers Darr and Tom Aley after prior data ventures and work at Amazon, D&B, and Dow Jones. Aidentified says it is experiencing rapid client adoption. The company will use the $10 million Series A to fund further development and expand its team. The Series A round is backed by the founders, private investment funds and a range of private and corporate investors and will remain open until the end of Q1 as it explores additional strategic partners.

Led · Series A · Nov 2023

Accelex offers data acquisition, analytics and reporting solutions for alternative investors and asset servicers, using proprietary AI and machine learning to automate extraction, analysis and sharing of unstructured private markets data. Its platform focuses on automating difficult-to-access data to deliver investment performance and transaction insights. The company serves clients whose combined asset base exceeds $1.5 trillion, invested in more than 13,000 private market funds across 4,000 asset managers. Accelex operates from offices in London, Paris, Luxembourg, New York and Toronto. The firm plans to use recent funding to expand operations, enhance product capabilities and deliver client success. Founded in 2018, Accelex targets increased automation and scalability for private markets data workflows. Accelex builds a financial data extraction, analysis and reporting platform that turns unstructured documents into structured data and insights for alternative investors. The product applies AI and machine learning to extract data from a wide range of documents and reporting, with an interface for last-mile validation and cross-team collaboration. The company says this automation streamlines investor operations and reduces time from receipt of document to actionable data. Accelex plans to use the new funding to further develop its product offering and to beef up client acquisition and support. Founded in 2019 and launched 12 months ago, the company reports strong client growth including Alberta Investment Management Corporation. Its clients’ combined asset base is reported at over $300 billion invested in 3,500 private market funds across 1,100 managers.