Sisense

Sisense was founded in 2004 in Tel Aviv by Adi Azaria, Aviad Harell, Guy Boyangu, Eldad Farkash, and Elad Israeli.

Updated 8 days ago Reviewed by 7wData

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Platform for embedding analytics and AI-powered dashboards into software products, with tools for building and consuming data insights.

Sisense was founded in 2004 in Tel Aviv by Adi Azaria, Aviad Harell, Guy Boyangu, Eldad Farkash, and Elad Israeli. Initially a research-focused company, it launched publicly in 2010 and evolved from a general-purpose BI tool into a specialist in embedded analytics. The platform now targets ISVs, product teams, and SaaS companies wanting to embed analytics into customer-facing applications, positioning itself as an "Analytics Platform as a Service" (AnPaaS).

Sisense raised $100 million in its Series F in January 2020, bringing total funding to $276–290 million across seven rounds. The company has remained private and raised no new capital since 2020, instead sustaining growth through profitability. In 2024, Sisense hit $184.8 million in ARR, a 32 percent increase from $140 million in 2023, serving approximately 2,000 customers across financial services, healthcare, supply chain, technology, and manufacturing.

The core product portfolio includes Sisense Fusion (cloud-native analytics engine), Compose SDK (a React-compatible, code-first toolkit for developers), and Sisense Embed (white-label embedding). In May 2025, the company launched Sisense Intelligence, a suite of generative AI capabilities including a natural language assistant, automated narrative generation, forecasting, and a Model Context Protocol (MCP) server that lets AI agents access data with governance controls. The move signals Sisense's bet that analytics will shift from standalone dashboards to AI-driven insights embedded in workflows.

Ariel Katz, a former Microsoft Power BI executive, became CEO in April 2023, replacing Amir Orad, who moved to Executive Chairman. The company cut workforce significantly—15 percent in July 2023 and another 13 percent in January 2024—reducing headcount from 800 to approximately 400 as it prioritized profitability over growth. Despite workforce reductions, Sisense achieved positive EBITDA and maintained strong positioning in embedded analytics.

Who buys this

SaaS companies and ISVs embedding analytics directly into their products
Enterprise product teams building customer-facing analytics experiences
Financial services, healthcare, and technology organizations with data-intensive operations
Companies seeking white-label, customizable analytics with strong governance controls

Publicly disclosed clients

Expedia
USA Swimming
Funraise
Barrios
PagerDuty
Philips
Skullcandy
Bigtincan

Strengths and what to watch

Strengths

Developer-first architecture with Compose SDK and code-first embedding, positioning itself for product engineers rather than traditional BI analysts
Strong market leadership in embedded analytics: G2 Leader status with 4.2-star rating from 1,040+ verified reviews across 2025
AI-native product strategy with Sisense Intelligence suite, MCP server integration, and ISO 42001 AI governance certification achieved in April 2026

Watch for

Significant workforce reductions (28 percent over six months, 2023–2024) may have strained execution capability and institutional knowledge retention
No new funding since January 2020 Series F; relying on profitability and positive EBITDA to fund growth despite decelerated revenue expansion
Strategic pivot from internal BI toward embedded analytics and away from traditional BI market—risks customer churn and constrains expansion in broader BI segment

Recent moves

Key Information

Industry: Business Intelligence
Founded: 2004
Employees: 501-1000
Headquarters: New York, NY

Frequently Asked Questions

What is Sisense?

Sisense is a platform for embedding analytics and AI dashboards into software products. Founded in 2004, it evolved from a general-purpose BI tool into a specialist in embedded analytics serving ISVs, product teams, and SaaS companies wanting analytics embedded in customer applications.

What are Sisense's main products?

Sisense Fusion is a cloud-native analytics engine. Compose SDK is a React-compatible, code-first toolkit for developers. Sisense Embed provides white-label embedding. In May 2025, Sisense launched Sisense Intelligence, a suite of generative AI capabilities including natural language assistant, automated narrative generation, and forecasting with Model Context Protocol integration.

Who uses Sisense?

Sisense serves 2,000+ customers across financial services, healthcare, supply chain, technology, and manufacturing. Notable clients include Expedia, PagerDuty, Philips, USA Swimming, and Bigtincan. The platform targets SaaS companies, ISVs, and enterprise product teams embedding analytics directly into customer-facing applications with white-label customization and governance controls.

What are Sisense's strengths?

Sisense holds G2 Leader status with a 4.2-star rating from 1,040+ verified reviews. Its developer-first Compose SDK appeals to product engineers. The company achieved ISO 42001 AI governance certification in April 2026. It's a market leader in embedded analytics with AI-native product strategy and strong governance controls.

How much revenue does Sisense generate?

Sisense hit $184.8 million in annual recurring revenue (ARR) in 2024, a 32 percent increase from $140 million in 2023. The company raised $100 million in Series F funding in January 2020, bringing total funding to $276–290 million, but has remained private and profitable since 2020 without seeking new capital.

What is Sisense Intelligence?

Sisense Intelligence, launched May 2025, is a generative AI suite embedding natural language assistants, automated narrative generation, forecasting, and a Model Context Protocol (MCP) server enabling AI agents to access data with governance controls. It signals Sisense's strategic shift from standalone dashboards to AI-driven insights embedded directly in workflows.

How Sisense compares

Direct head-to-head against 3 competitors. Picked by 7wData.

Positioning: Platform for embedding analytics and AI-powered dashboards into software products, with tools for building and consuming data insights.
Customer segments: SaaS companies and ISVs embedding analytics directly into their products
Strengths: Developer-first architecture with Compose SDK and code-first embedding, positioning itself for product engineers rather than traditional BI analysts
Watch for: Significant workforce reductions (28 percent over six months, 2023–2024) may have strained execution capability and institutional knowledge retention
Recent moves: Sisense launches Sisense Intelligence: AI-powered analytics suite with natural language assistant, forecasting, and MCP server integration

Positioning: Agentic analytics platform treating embedded deployment as first-class, targeting enterprise SaaS vendors and Fortune 100 data teams.
Customer segments: Enterprise SaaS vendors, Fortune 100 data teams, and technology companies needing embedded natural language analytics for end customers.
Strengths: Natural language search on live warehouse data, with ThoughtSpot Everywhere treating embedding as a first-class product rather than an add-on.
Watch for: Consumption-based pricing regularly exceeds $500K annually for mid-market deployments, making cost unpredictable for ISVs scaling embedded usage.
Recent moves: September 2024: Ketan Karkhanis, former Salesforce Sales Cloud EVP, appointed CEO amid a push toward agentic analytics positioning.

Positioning: Google Cloud governed analytics layer for enterprises on BigQuery, offering embedded BI via LookML semantic control for product teams.
Customer segments: Mid-to-large enterprises on Google Cloud, data engineering teams, and product teams embedding governed analytics into GCP-based applications.
Strengths: LookML semantic layer enforces a single metric definition across all embedded reports, preventing definition drift in large engineering organizations.
Watch for: Customers on non-Google stacks cite deep BigQuery dependency: multi-cloud or Snowflake-first teams face feature gaps and migration friction.
Recent moves: April 2026: Looker BI Agents launched at Google Cloud Next 26, enabling analytics to trigger downstream business actions via the semantic layer.

Positioning: Enterprise data-to-AI platform spanning data integration and embedded analytics at scale, targeting ISVs and large regulated-industry organizations.
Customer segments: ISVs, financial services, manufacturing, healthcare, and government agencies needing analytics and data movement consolidated under one vendor contract.
Strengths: Unified pipeline from ingestion (Talend, Upsolver) through embedded analytics lets ISVs consolidate data integration and BI under a single vendor.
Watch for: April 2026 outages caused by a Microsoft security patch breaking QlikView authentication, signaling recurring reliability risk on enterprise deployments.
Recent moves: January 2025: Acquired Upsolver for real-time data streaming and Apache Iceberg optimization, expanding data integration capabilities.

Sources

www.sisense.com — Company overview, products (Sisense Fusion, Compose SDK, Sisense Embed), customer base, mission
getlatka.com — 2024 revenue ($184.8M ARR), customer count (2,000+), year-over-year growth (32%), employee count (598)
www.businesswire.com — Sisense Intelligence launch date (May 28, 2025), AI capabilities (assistant, narrative, forecasting, MCP), AnPaaS positioning
www.techtarget.com — AI features strategy, Ariel Katz CEO statement on GenAI bottlenecks, 2026 product roadmap including agents and semantic layer
www.calcalistech.com — July 2023 layoffs (100 employees, 15% workforce), January 2024 layoffs (60 employees, 13%), workforce reduction from 800 to 400, ARR of $150M and positive EBITDA
www.g2.com — G2 rating (4.2 stars), customer reviews count (1,040+), customer satisfaction leadership in embedded BI
www.sisense.com — Ariel Katz promotion to CEO (April 2023), Amir Orad transition to Executive Chairman, Katz's Microsoft background and Power BI experience
finance.yahoo.com — ISO/IEC 42001:2023 certification (April 28, 2026), AI governance framework, Schellman Compliance audit