Sisense

Sisense

Paid

AI-powered analytics platform for building, embedding, and composing data experiences into any application with generative AI and a flexible cloud architecture.

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What is Sisense?

Sisense is an analytics platform built primarily for embedding rather than internal dashboards. Its Compose SDK offers a code-first, composable approach so product teams can build data experiences into their own applications rather than iframing someone else's dashboard, and it adds a generative AI assistant, an MCP server for agent access, white-labelling and multi-tenant architecture for serving many customers from one deployment. Pricing is entirely quote-based and reported figures vary widely, which itself tells you something. Independent estimates put the practical floor around $10,000 to $25,000 a year for small internal deployments, with credible embedded projects reported between roughly $40,000 and $90,000 in year one once professional services are counted. Three line items consistently inflate quotes: mandatory first-deployment services, white-label and multi-tenant capacity as add-ons rather than inclusions, and data-volume overages.

Key Features

Compose SDK Embedded AnalyticsSisense Intelligence GenAIMCP Server for AI AgentsDrag-and-Drop Dashboard BuilderCloud-Native ArchitectureData Modeling ToolWhite-Label AnalyticsConnectivity to 100+ SourcesRow-Level SecurityCustom VisualizationsAPI-First ArchitectureGit IntegrationHIPAA and SOC 2 ComplianceFinancial Services AnalyticsMarketplace Extensions

How to Use Sisense

1Connect Sisense to your data sources using 100+ connectors or the built-in data modeling tool
2Build dashboards and reports with the drag-and-drop interface or use the SQL editor for advanced queries
3Embed interactive analytics into your product using Compose SDK with a few lines of code
4Enable the Sisense Intelligence AI assistant to let users ask questions in natural language
5Set up governance, row-level security, and access controls for multi-tenant deployments

✅ Best For

  • SaaS companies and ISVs building analytics-as-a-feature inside their own product who need a flexible, API-first embedded analytics platform that handles multi-tenancy, white-labeling, and AI-generated insights out of the box.
  • Enterprise teams in financial services, healthcare, and supply chain that need a composable, AI-powered analytics platform integrating with their existing application stack via the MCP server and Compose SDK.

❌ Not For

  • Teams primarily looking for a self-serve BI tool for internal reporting and exploration, as Sisense is optimized for embedded analytics in product rather than standalone internal dashboards.
  • Non-technical business users who need a simple, plug-and-play analytics experience without developer involvement, as getting the most out of Sisense typically requires a data or application development team.

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Pricing

GrowCustom
  • ✓Core analytics
  • ✓dashboards
  • ✓standard embedding
EnterpriseCustom
  • ✓Full Compose SDK
  • ✓white-label
  • ✓AI assistant
  • ✓governance
Enterprise+Custom
  • ✓Dedicated infrastructure
  • ✓HIPAA
  • ✓custom SLAs
  • ✓MCP server

Prompts to Try

Build an embedded analytics dashboard showing my SaaS customers their own product usage data

How do I use the Compose SDK to add a revenue chart to my application?

Set up row-level security so each tenant only sees their own data

Enable the Sisense AI assistant for natural language queries on my embedded dashboard

Connect my Snowflake data warehouse and build a financial performance report

Use Cases

A B2B SaaS company uses Sisense's Compose SDK to embed a white-labeled product usage analytics panel into their customer portal, increasing feature adoption and reducing customer support tickets by 22%.
A fintech startup uses Sisense's multi-tenant embedded analytics to give each of their 500 business clients a branded, real-time financial performance dashboard within the startup's own product.
A healthcare data platform uses Sisense Intelligence and the AI assistant to let clinical administrators ask natural language questions about patient throughput and bed utilization, getting instant answers from governed hospital data.
A supply chain software company integrates Sisense via the MCP server into their AI-powered procurement agent, enabling the agent to query live inventory and supplier performance data when making autonomous reorder decisions.
A manufacturing analytics team uses Sisense's Git integration to version control their dashboard definitions and semantic models, enabling code-review workflows for analytics changes similar to their software development process.

Frequently Asked Questions