Kinetica, the speed layer for generative AI and real-time analytics, has announced a native Large Language Model (LLM) combined with Kinetica’s innovative architecture that allows users to perform ad-hoc data analysis on real-time, structured data at speed using natural language. Unlike with public LLMs, no external API call is required and data never leaves the customer’s environment. This announcement follows Kinetica’s earlier innovation as the first analytic database to integrate with OpenAI.
In addition to being more secure, Kinetica’s native LLM is tailored to its syntax and industry data definitions such as telecommunications, financial services, automotive, logistics and others, creating more reliable and accurate SQL generation. This capability extends beyond standard SQL, ensuring efficient handling of intricate tasks for enhanced decision-making for time-series, graph, and spatial questions. Kinetica’s approach to fine-tuning prioritizes SQL generation optimization to ensure consistent and accurate results, versus more common techniques that prioritize creativity that yield diverse but unpredictable responses. This guarantees ongoing functionality for businesses and users, offering peace of mind in SQL query outcomes.
“Kinetica has led the market with next-level capabilities for analyzing sensor and machine data with our vectorized, real-time analytic database,” said Nima Negahban, Cofounder and CEO, Kinetica. “With the integration of SQL-GPT, we extend this capability to an entirely new horizon, empowering organizations to unleash the true potential of their real-time, structured data like never before.”
The U.S. Air Force has been working with Kinetica, leveraging advanced analytics on sensor data to quickly identify and respond to potential threats, helping to keep the skies safe and secure for all users of the national airspace system. The U.S. Air Force is now using Kinetica’s embedded LLM to detect threats in our airspace and identify anomalies using natural language.
“At Kinetica, we believe in fostering openness and embracing the diversity of generative AI models,” said Amit Vij, Cofounder and President, Kinetica. “We expect there will be different LLM platforms that emerge and we want to provide our customers with choice. While currently supporting two models, our commitment lies in continuously expanding our offerings to accommodate client-driven preferences and seamlessly integrate with a wide array of future models. Towards that end, Kinetica will roll out integration with other LLM platforms like NVIDIA NeMo later this year for language to SQL as new state of the art models emerge.”
Kinetica’s native LLM is now available to customers in a containerized, secure environment either on-premises or in the cloud.