Our product portfolio is the result of our extensive experience with Search and Big Data technologies as well as our long-term relationships with customers.
Logsene is an affordable centralized log management and analytics solution available in the cloud and on premises. You can send your logs to Logsene for indexing and make them instantly searchable with nothing to install or maintain. It exposes syslog (rsyslog) and Elasticsearch API endpoints, consumes logs from syslog, Logstash, Flume, Fluentd, etc., It exposes multiple user interfaces, including Kibana. It integrates with SPM to correlate logs with performance metrics, alerts, anomalies, and events.
Sematext Site Search Analytics (SSA) is the enterprise-class, cloud-based, search vendor-neutral Site Search Analytics SaaS. It is a reliable, scalable, and flexible Search Analytics solution that you can start using within minutes without having to develop, set up, manage, or scale your own query log analysis tools and infrastructure. Sematext Search Analytics lets you view up-to-the-minute Search Analytics graphs, charts, and tabular data, spot trends, cut, and slice data by time, by query origin or type, and other dimensions.
Businesses use Sematext Site Search Analytics to collect and analyze user search behavior data, clickstream data, and search-related transactions. This provides them with insight about their customers' search experience, the quality of search results, and a mechanism to qualitatively measure any changes made to search engine backend, and more. Ultimately, Site Search Analytics allows businesses to continuously measure, monitor, and improve the search experience and ultimately increase their bottom line.
Sematext Search AutoComplete enhances the search experience by adding the auto-complete functionality to any search form. AutoComplete is known to reduce query misspellings and typos, to lead searchers to their targets faster, with less cognitive and typing effort, and leaving less room for error.
Query Relaxer is a Solr component that improves search experience. It executes alternative queries when it detects that original query produced poor results or no results at all due to being too restrictive. It transparently returns better search results to the client without the client having to restructure the query and send additional requests to Solr over the wire and re-examine the results.
Related Searches offer the familiar "People Who Searched For This, Also Searched For..." functionality. When a person runs a query X, the Related Searches service offers several other queries other people who run the same X query have performed. You may have seen this functionality on Google's search results pages, and possibly in commercial enterprise search vendors' offerings.
Performance Monitoring (SPM) is an enterprise-class, server and application performance monitoring, alerting, and anomaly detection solution. It is available both in the cloud (SaaS) and on premises, and it integrates with Logsene to correlate metrics, alerts, anomalies, and events with application and server logs.
SPM is a reliable, scalable, and flexible monitoring solution that you can start using within minutes without having to set up, manage, or scale your own monitoring systems and infrastructure. SPM lets you view up-to-the-minute performance graphs and charts, spot trends, narrow reports by time, by server, and by other application-specific dimensions.
Developers and system administrators use SPM to collect and track performance metrics, gain system-wide insight into operational health, resource utilization and performance of their systems, and can react immediately to keep their applications and businesses running smoothly.
Key Phrase Extractor is a toolkit for extracting key terms (key words) and phrases from text. Key Phrase Extractor is an excellent tool for extraction of popular terms and phrases from a text data stream, such as from news and social media (e.g. blogs, tweets, feeds)!.
DYM ReSearcher (DYMRS) is a Solr component that improves search experience. It executes alternative queries when it detects that original queries produced poor results or no results at all due to spelling mistakes or typos. It transparently returns better search results to the client.
Query Segmenter detects known entities by analyzing a query and rewriting it to make it more precise. For example, it may take a query such as "female red dress" and restructure it as "gender:female color:red name:dress". When used with geospatial searches it can take a query like "beergarten brooklyn" and restructure it as "beergarten city:brooklyn within N miles from lat,lon", where N can be configured and "lat,lon" can be injected (e.g. lat,lon may represent the location of the person performing the query, which can be very handy for search on mobile applications).