sisense

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1. 11/2/2026

   Updated: best for, features, integrations, sources, summary, use cases, walkthrough

   See recorded changes

   bestFor

   Before: ["Enterprises and regulated industries requiring high security, uptime, and control for embedded analytics.","Startups and growing teams needing quick deployment of embedded analytics with AI capabilities."]

   After: ["Enterprises and regulated industries requiring secure, compliant embedded analytics","Startups and growing teams needing quick, self-serve embedded analytics"]

   features

   Before: ["Governed semantics and shared formulas to maintain consistent metrics.","Tenant-safe access and row-level security to keep customer data isolated.","Semantic enrichment and publishing semantics to help AI understand data.","Flexible APIs, SDKs, embed paths, and multi-tenant architecture for embedding AI into products.","Natural language query support with assistant and search to find insights without navigating dashboards."]

   After: ["Governed AI analytics with consistent metrics and shared formulas","Tenant-safe access and row-level security to protect customer data","Natural language query assistant and search for insights","Narrative explanations and insight summaries to clarify complex results"]

   integrations

   Before: ["Connect Sisense data to AI tools and workflows using MCP or APIs."]

   After: []

   sources

   Before: [{"url":"https://www.sisense.com/","label":"AI-Powered Embedded Analytics Platform - Sisense"},{"url":"https://www.sisense.com/plans/","label":"AI analytics plans | Sisense"}]

   After: [{"url":"https://www.sisense.com/","label":"AI-Powered Embedded Analytics Platform - Sisense"},{"url":"https://www.sisense.com/plans/","label":"AI analytics plans | Sisense"},{"url":"https://www.sisense.com/success/billion-dollar-analytics-for-all-how-iquantiv-helps-clients-unlock-2-more-gross-margin/","label":"Billion-dollar analytics for all: How iQuantiv helps clients unlock 2% more gross margin | Case Stusy"}]

   summary

   Before: "Governed semantics and shared formulas to maintain consistent metrics. Tenant-safe access and row-level security to keep customer data isolated."

   After: "Embedding AI-powered analytics into customer-facing products for real-time insights. Governed AI analytics with consistent metrics and shared formulas. Tenant-safe access and row-level security to protect customer data."

   useCases

   Before: []

   After: ["Embedding AI-powered analytics into customer-facing products for real-time insights","Providing executives with self-service analytics for strategic decision-making"]

   walkthrough

   Before: ["Connect data, model it, and embed analytics in your app using flexible APIs and SDKs.","Use Compose SDK and APIs to control where intelligence appears and how it behaves in your product.","Generate Compose SDK embed code, work across multiple frameworks, and extend experiences with custom plugins."]

   After: ["Connect data, model it, and embed analytics into your app using flexible APIs and SDKs","Use Compose SDK and APIs to control where intelligence appears and how it behaves","Let users ask questions in plain language and get insights without navigating dashboards"]

2. 9/14/2026

   Updated: best for, features, integrations, plans, platforms, walkthrough

   See recorded changes

   bestFor

   Before: []

   After: ["Enterprises and regulated industries requiring high security, uptime, and control for embedded analytics.","Startups and growing teams needing quick deployment of embedded analytics with AI capabilities."]

   features

   Before: ["Governed semantics and shared formulas to maintain consistent metrics.","Tenant-safe access and row-level security to keep customer data isolated.","Semantic enrichment to help AI understand data with controlled guidelines.","Flexible APIs, SDKs, and embed paths for integrating AI into products.","Narrative explanations and driver analysis to clarify complex results."]

   After: ["Governed semantics and shared formulas to maintain consistent metrics.","Tenant-safe access and row-level security to keep customer data isolated.","Semantic enrichment and publishing semantics to help AI understand data.","Flexible APIs, SDKs, embed paths, and multi-tenant architecture for embedding AI into products.","Natural language query support with assistant and search to find insights without navigating dashboards."]

   integrations

   Before: []

   After: ["Connect Sisense data to AI tools and workflows using MCP or APIs."]

   plans

   Before: []

   After: [{"name":"ENTERPRISE","note":"Contact the provider for a quote.","annual":null,"monthly":null,"perSeat":false,"currency":"USD","features":[],"extraUnit":null,"unitLabel":"","maximumSeats":null,"minimumSeats":1,"includedUnits":null,"startingPrice":false,"seatsConfirmed":false}]

   platforms

   Before: ["Supports deployment on AWS, Azure, and Google Cloud Platform."]

   After: []

   walkthrough

   Before: ["Developers can embed analytics using iframe or Compose SDK across multiple frameworks and extend with custom plugins."]

   After: ["Connect data, model it, and embed analytics in your app using flexible APIs and SDKs.","Use Compose SDK and APIs to control where intelligence appears and how it behaves in your product.","Generate Compose SDK embed code, work across multiple frameworks, and extend experiences with custom plugins."]