Sisense

Sisense is an embedded analytics platform that puts BI dashboards and AI answers inside a software maker's own app, run in the cloud or on-premises.

Sisense turns company data into charts, reports and plain-language answers that appear inside the applications people already use. Rather than sending customers to a separate reporting tool, a software maker builds analytics into its own product with Sisense underneath. Sisense Ltd. develops it from offices in New York and Ramat Gan, Israel. The same platform also serves internal teams that want governed dashboards drawn from a cloud warehouse. Data arrives through ElastiCube models, which import and rebuild on a schedule, or through live models that query a warehouse such as Snowflake directly. Analysts shape it with custom tables, columns and import queries, then define a semantic layer that every dashboard shares. The Widget Designer builds charts from chosen fields, and a selection on any chart filters the dashboard or drills deeper. Simply Ask answers natural-language questions with a visualisation, while Sisense Intelligence adds auto-narratives and built-in predictive analytics add forecasts and anomaly detection. Dashboards export as paged PDF reports, go out by email through the Sisense Scheduler, and open in Sisense Mobile on Android and iPhone. Product and engineering teams that owe their customers analytics are the core audience, from startups shipping a first dashboard to enterprises in regulated industries. Its industry solutions cover healthcare, financial services, supply chain, technology and manufacturing. Developers embed the work by iframe or with the Compose SDK, and enterprise buyers can run it as SaaS, in a dedicated cloud or on their own servers. Smaller teams sign up for the Self-Serve plan, and larger organisations arrange the Enterprise plan with the sales team. A common job is a SaaS company giving every customer a dashboard that shows only that customer's records, enforced by data security rules at row level. Another is a data team pointing live models at Redshift so reports read current figures without a nightly copy. Releases move from development to production by promoting data models and dashboards through version control. Where a source database sits behind a firewall, an SSH tunnel or VPN reaches it without opening a direct connection. Sisense fits wherever analytics has to ship as part of another company's product.