KX and Engine AI today announced a partnership to deliver a native, productive AI platform for clients in the global financial services sector.
Supporting advanced use cases such as similarity search, recommendation systems and pattern matching capabilities, this partnership is set to revolutionize the way organizations approach commercial decision-making and execution performance, while enhancing end-user productivity and seamlessly integrating into existing workflows.
Farhang Mehregani, CEO, Engine AI:
“We empower our customers to monetize the value of their data with native AI data analytics applications. Our powerful, open, end-to-end enterprise platform and intuitive Data Analytics Co-pilot are designed to unlock the full potential of AI and data analytics. We are excited to partner with KX, which offers excellent vector and time series database capabilities, making them an ideal partner for the financial sector.”
Ashok Reddy, CEO, KX:
“KDB.AI brings timing and situational awareness to productive AI applications while providing a superior developer experience. These capabilities, combined with Engine AI’s expertise in application delivery, are game-changers for retail and institutional customers looking to take advantage of the transformative potential of genetic AI. Together, we accelerate our customers’ abilities to address the most complex, high-frequency Financial Services use cases, significantly reducing the time to insight from big data. We are not only meeting the current AI-driven demands of our customers, but also pushing the boundaries to redefine the future of smart finance.”
KDB.AI offers advanced search capabilities, enabling developers to bring hybrid similarity, fuzzy, temporal and real-time search to their AI-based applications. Designed to handle high-velocity, time-series data and multi-mode query data processing, it democratizes access to real-time data analytics, enabling business users to search live financial market information through natural language search.
Additionally, its seamless integration with popular LLM and machine learning streams and tools, including LangChain and ChatGPT, and native support for Python and RESTful APIs means developers can perform common functions using their preferred applications and languages.