Great news from Siren who have announced a major product launch. This has been in the works for some time and we have been supporting the staff as they toil away here at GTC.
What is Siren 10.3? Straight from the company website, it offers 5 distinct core AI capablities:
Deep learning-based predictive analytics and alerting(Siren ML) – real-time forecasting of operational data streams and alerting on expected future crossing of set thresholds.
Deep learning-based time series anomaly detection (also in Siren ML) – the capability of learning from data to recognize and alert for anomalous behavior. Unlike other offerings on the market, Siren offers this based on automatic model selection ML, powered by Dockerized TensorFlow-backed APIs with seamless front-end integration.
Unstructured data discovery with real-time topic clustering – Discover meaningful clusters within textual documents (reports, emails, news articles, and so on), based on auto-discovery of key terms and topics, with the new Topic Explorer, a built-in real-time interactive clustering visualization.
Associative in-dashboard Relational Technology (“Dashboard 360”) – Siren dashboards now allow the definition of an “internal data model” by which visualizations on different tables (searches) can coherently display only data from “connected records” at each step. This provides a 360-degree view of a record (or groups of records), showing in a single view what is connected (both directly and indirectly, via many relations). What makes this feature unique on the market is that you can filter each of the interconnected visualizations, and all the others will update coherently to only show records that are not filtered out (as they are not associated).
This “associative” drill-down capability has, up to now, only been (partially) available on high-end Business Intelligence (BI) systems; these systems, however, require all data to be in memory, thus sacrificing scalability and real-time capabilities. With Siren Dashboard 360, this associative drill-down capability is now available at big data scale, in real time, on Elasticsearch or other backends.
State-of-the-art, self-correcting entity resolution (Siren ER) – this is the AI/ML ability to recognize that records across different tables and datasources, using different schemas and different languages, are in fact talking about the same entity (person, company). Siren ER is real-time and capable of “self-correcting” previous statements as new information arrives.
For More Information go to the website: