Dataminr operates a constellation of more than 60 purpose-built, specialized LLMs, trained on the company’s proprietary 10+ year archive of historical event data. Dataminr’s AI model approach ensures the speed, precision and superior accuracy that corporate security teams demand from real-time intelligence.
Dataminr first created and integrated our own LLMs in 2019, long before the LLM and GenAI boom. Dataminr’s internal LLMs and AI models are built, trained, and run by a team of 150+ AI experts, including over a dozen PhD-level AI scientists and researchers.
Dataminr first pioneered Multi-Modal Fusion AI — synthesizing text in 150 languages, image, video, audio, and sensor signals across 1M+ public data sources — to deliver the fastest, most accurate real-time alerting.
Seamlessly integrated with Dataminr’s real-time alerts, Dataminr Advanced for Corporate Security delivers three new AI-powered autonomous intelligence capabilities — all continuously and autonomously corroborating, contextualizing, and anticipating in real time from the moment of first event discovery.
Coupled with Autonomous Real-Time Intelligence, Dataminr Advanced for Corporate Security also includes a broader set of new capabilities that significantly increase the product’s value across its browser-based, mobile, and API interfaces.
A surge in global risk makes it harder for corporate security teams to get ahead and act as strategic partners. With Agentic Corroboration, Agentic Context, and Near-Term Predictive Intelligence, organizations know what happened, why it matters, and what happens next as an event unfolds — closing the gap between detecting a threat and acting on it.
Dataminr is an absolute gem in regards to identifying things before they happen.”
Executives have no hesitation acting on the information we get from Dataminr.”
Dataminr is really a key resource for our program—including how we assess threats and manage incidents.”
If we did not have the Dataminr tool and we weren’t alerted to the information that we were, our staff would have been exposed to added risk where their safety and security could have been compromised.”
