KX and Engine AI announced today a partnership to offer a native, generative AI platform for clients in the global financial services sector.
Supporting advanced use cases including similarity search, recommendation systems, and pattern matching capabilities, this collaboration is set to revolutionize the way organizations approach trading decision-making and execution performance while boosting end-user productivity and seamlessly integrating within existing workflows.
Farhang Mehregani, CEO, Engine AI:
“We empower our clients to monetize the value of their data with AI-native data analytics applications. Our powerful, open, end-to-end enterprise platform and intuitive Data Analytics Co-pilot all engineered to unlock the full potential of AI and data analytics. We are thrilled about our partnership with KX, who offer exceptional vector and time-series database capabilities, making them the ideal partner for the financial sector”.
Ashok Reddy, CEO, KX:
“KDB.AI brings time and situational awareness to generative AI applications, while providing a superior developer experience. These capabilities, combined with Engine AI’s expertise in application delivery, is a game changer for retail and institutional clients looking to benefit from the transformative potential of generative AI. Together, we accelerate our clients’ abilities to address the most complex, high-frequency Financial Services use cases, significantly reducing time to insight from large data. We’re not only meeting our clients’ current AI-driven demands but also pushing the boundaries to redefine the future of intelligent finance”.
KDB.AI offers advanced search capabilities, empowering developers to bring hybrid similarity, fuzzy, temporal, and real-time search to their AI-driven applications. Built to handle high-speed, time-series data and multi-mode query data processing, it democratizes access to real-time data analytics, enabling business users to conduct searches on live financial market information through natural language search.
Moreover, its seamless integration with popular LLMs and machine learning workflows and tools, including LangChain and ChatGPT, and native support for Python and RESTful APIs means developers can perform common operations using their preferred applications and languages.