Can I use my own large language model (LLM) with Sisense AI?

Yes, the Enterprise plan allows you to bring your own LLM, giving you control over the AI models used within your governed analytics environment.

How does Sisense handle data security for multiple customers in one deployment?

It uses a native multi-tenant architecture with row-level and column-level security enforced at the query layer to ensure complete data isolation between tenants.

What is the Compose SDK used for?

The Compose SDK is a set of tools for developers to embed Sisense analytics components directly into their product's UI, offering more control than iframe embedding.

Does Sisense support on-premise deployment?

Yes, the Enterprise plan offers deployment on SaaS, your own cloud (AWS, Azure, GCP), or on-premise to meet data sovereignty and compliance requirements.

What kind of data connectivity does the platform support?

Sisense connects to a wide range of sources including cloud data warehouses, traditional databases, and SaaS apps, with advanced options for SSH/VPN for secure connectivity.

Directory/Analytics/AI Assistants/Sisense

Sisense

Sisense is a composable, AI-powered analytics platform designed for embedding into customer-facing products and applications. It provides a full-stack solution for data connectivity, modeling, visualization, and AI-driven insights, allowing companies to offer governed analytics under their own brand. Key capabilities include a multi-tenant architecture for secure, isolated data, a semantic layer for consistent metrics, and a suite of AI tools for natural language queries, automated narratives, forecasting, and trend analysis. It connects to any data source and offers flexible embedding via APIs, SDKs, or iframes. Target users are software development teams, product managers, and founders building SaaS or embedded analytics products. It's used in regulated industries like finance and healthcare, as well as by tech companies to enhance their product offerings with data intelligence.

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Added on

Sep 22, 2026

Embedded analyticsAI analytics platformNatural language queriesMulti-tenant architectureCompose SDKHIPAA-readyBring your own LLM

Product information

Everything worth knowing about Sisense

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

Embedded Analytics & APIs

Embed analytics into your product via lightweight widgets to custom builds using Compose SDK and APIs. Connect AI experiences using MCP or APIs.

Natural Language Query & AI Assistant

Allow users to ask questions in plain language with an AI assistant, and search for insights without navigating complex dashboards.

Data Narrative & Explanation

Automatically turn complex results into clear summaries and explain the drivers behind changes in your data.

Forecasting & Trend Analysis

Surface future trends and changes proactively using forecasting, pulse, and trend analysis tools.

Technical capabilities

Multi-Tenant Architecture & Security

Maintain tenant-safe access and row-level security at the query layer, preventing data leakage between customers. Supports HIPAA-ready compliance, column-level security, and SSO.

Governed Semantics & AI Context

Use governed semantics and shared formulas so people and AI work from the same approved definitions. Provide context to AI via semantic enrichment.

Must watch videos

AI-Powered Analytics for Smarter Insights: Sisense Intelligence (Success Series)

33:30

Tutorial33:30

AI-Powered Analytics for Smarter Insights: Sisense Intelligence (Success Series)

Stop digging through data and start finding answers. In this video, we dive into Sisense Intelligence, a powerful suite of AI tools designed to help creators, developers, and end-users scale their analytics faster than ever. Learn how Sisense uses Machine Learning to automate complex data analysis, providing you with high-level narratives and deep-dive explanations in seconds. Key Features Covered: * AI Assistant: Your partner for on-the-fly data questions. * Explanations: Instantly uncover the "why" behind data spikes and anomalies. * Forecasting: Use ML to predict future trends and optimize revenue. * Narratives & Trends: Turn raw data into easy-to-read stories for stakeholders. 🚀 Ready to scale your analytics? Visit https://docs.sisense.com/main/SisenseLinux/ai-overview.htm to learn more about Sisense Intelligence. #Sisense #AIAnalytics #BusinessIntelligence #DataScience #MachineLearning #SisenseIntelligence Learn more at www.sisense.com

Sisense Intelligence: The AI-powered analytics that builds with you

1:22

Tutorial1:22

Sisense Intelligence: The AI-powered analytics that builds with you

Whether you're building products, designing data workflows, or embedding insights into your app, Sisense Intelligence is your new AI-first suite of tools. In this short animated video, we show you how Sisense Intelligence helps you accelerate creation, embed with ease, and democratize data literacy. Discover the power of a complete analytics platform that enhances both the developer and end-user experience. With Sisense Intelligence, you'll: Build with natural language: Use the assistant to create visualizations and build with ease just by asking. Extract the story: Instantly convert dashboards into an understandable narrative with the narrative feature. Know the future: Identify patterns to help you plan ahead using forecast and trend. Get behind the scenes: Instantly see what's driving changes in your metrics with explanation. And with Compose SDK, you can use your framework of choice to embed these AI-driven analytics into your apps. Ready to discover the AI-powered analytics that give your product strategy a competitive edge? Learn more at https://www.sisense.com/ai-analytics-platform/generative-ai-analytics/

How does Sisense stay on top of API Attacks?

2:52

Tutorial2:52

How does Sisense stay on top of API Attacks?

Sisense powers analytics experiences inside the applications businesses rely on every day. As an API-first platform, securing those connections is critical, especially as AI agents increasingly operate through APIs to access data and trigger workflows. In this conversation, Sangram, CISO and VP of IT at Sisense, and Michael Callahan, CMO at Salt Security, discuss how Sisense approached API security strategically to protect their platform, maintain customer trust, and support innovation in the Agentic AI era.

Who uses it

Real use cases, no hype

Embedded Analytics in SaaS Products

Integrate analytics dashboards and AI insights directly into your customer-facing software under your own brand.

Customer-Facing AI Insights

Deploy governed generative AI features that answer user queries using your approved metrics and data context.

Multi-Tenant Data Services

Serve analytics to multiple clients with strict data isolation and row-level security in a single platform instance.

Enterprise Business Intelligence

Provide governed self-service analytics and reporting for internal teams, with advanced data modeling and connectivity.

Regulated Industry Compliance

Deploy analytics with built-in controls for HIPAA, column-level security, and detailed audit trails.

Mobile & Web App Analytics

Embed lightweight analytics widgets or full dashboards into mobile and web applications using flexible SDKs.

What's great

Strong AI integration for natural language queries and automated insights.
Comprehensive data connectivity to warehouses, databases, and cloud apps.
Proven track record with enterprise customers in regulated industries.
White-labeling and full branding control for embedded products.

Technical strengths

Deep embedding flexibility with Compose SDK for custom product integration.
Robust multi-tenant architecture with row-level security for customer data isolation.
Enterprise-grade deployment options: SaaS, dedicated cloud, or on-premise.

Where it falls short

Complex pricing and sales process for enterprise plans.
Self-serve plan may lack advanced features needed for complex analytics.
Steep learning curve for advanced data modeling and security configuration.

Technical limitations

Heavy reliance on their proprietary data modeling layer.
Potential vendor lock-in due to deep integration of Sisense-specific AI and semantics.
Limited transparency on AI model specifics beyond 'bring your own LLM'.

For technical folks

The deep-dive specs

FAQ

Includes technical Q&A

Self-Serve is for startups to embed basic analytics quickly with a free tier. Enterprise is for regulated industries needing multi-tenancy, on-prem deployment, dedicated support, and a 99.99% SLA.