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Sisense

Sisense is an AI-powered platform that enables organizations to connect, model, analyze, and visualize data from multiple sources, facilitating embedded within applications and driving data-informed decision-making. Founded in 2004 in , , by Elad Israeli, Eldad Farkash, Aviad Harell, Guy Boyangu, and Adi Azaria, Sisense initially focused on simplifying complex data analysis for non-technical users through innovative software that handles large datasets efficiently. The company relocated its headquarters to in 2017, establishing a global presence with offices in , Scottsdale, , , and other locations, and employs approximately 650 professionals serving more than 2,000 customers across industries like , healthcare, and , as of 2024. Sisense's core platform supports over 400 data connectors, generative for conversational and automated modeling, and flexible deployment options including cloud-based and on-premises solutions, with certifications such as SOC 2 Type II and ISO 27001. In , the company experienced a incident compromising some . Key milestones include raising $50 million in Series D funding in 2016, acquiring Periscope Data in 2019 to enhance cloud capabilities, and securing $100 million in 2020 at a valuation exceeding $1 billion, marking its status. Sisense achieved profitability in 2022. Under CEO Ariel Katz since 2023, the company continues to emphasize API-first composability for custom app integrations.

History

Founding and Early Development

Sisense was founded in 2004 in , , by Elad , Eldad Farkash, Aviad Harell, Guy Boyangu, and Adi Azaria. The founders, who began as a group of undergraduate students working on a college project, aimed to transform complex data analytics into a more accessible and efficient process through innovative technical approaches. Their vision centered on making data analytics fluent, easy, and fast, addressing the limitations of traditional tools that were often cumbersome for non-technical users. From its inception, Sisense focused on developing in-memory data processing technology, specifically through its proprietary ElastiCube engine, a columnar designed to handle complex datasets efficiently without requiring extensive hardware resources. This innovation allowed for rapid querying and analysis of large volumes of data, setting the company apart in the early landscape by enabling agile analytics on commodity hardware. The initial years were dedicated to research and development, refining this technology to process billions of rows of data while minimizing the need for specialized infrastructure. In 2010, Sisense launched its first commercially available product, Prisms, which emphasized agile by integrating the ElastiCube technology to deliver fast, interactive dashboards and reports. This release marked the company's shift from internal development to market entry, coinciding with a $4 million Series A round that supported initial U.S. efforts. Subsequent rounds built on this early product success to fuel further growth. As Sisense transitioned from a small founding team to broader operations, it encountered challenges in scaling its technology and team to meet international demands, particularly as it established a presence to serve a growing global customer base. This period involved adapting the platform for diverse enterprise needs while maintaining performance efficiency, laying the groundwork for its evolution into a full-stack analytics provider.

Funding Milestones and Growth

Sisense secured its initial significant external funding in July 2010 with a $4 million from investors including Partners and Scale Venture Partners, enabling early product commercialization and U.S. market entry. In April 2013, the company raised $10 million in a Series B round led by , with participation from Opus Capital and existing backers, to fuel international expansion and analytics development. By June 2014, Sisense completed a $30 million Series C funding round led by DFJ Growth, alongside and , bringing total capital raised to over $53 million and supporting enhanced platform scalability for enterprise clients. This growth trajectory continued in January 2016 with a $50 million Series D investment from , DFJ Growth, , and Genesis Partners, aimed at accelerating in embedded analytics and global operations. In September 2018, Sisense announced an $80 million Series E round led by Insight Venture Partners, with contributions from prior investors, elevating total funding to approximately $200 million and positioning the company for aggressive hiring and product maturation in cloud-based business intelligence. The momentum peaked in January 2020 with a $100 million Series F extension led by Insight Venture Partners, valuing Sisense at over $1 billion and granting it unicorn status, while emphasizing advancements in embedded analytics solutions. These investments facilitated strategic moves, such as the 2019 acquisition of , which integrated advanced data preparation capabilities into Sisense's offerings. Overall, Sisense has raised more than $274 million across multiple rounds, driving revenue growth to an annual recurring rate of $150 million by 2023 and expanding its customer base to over 2,000 enterprises worldwide. This financial foundation has supported sustained scaling into 2025, with continued focus on AI-driven analytics innovation.

Acquisitions and Strategic Expansions

In May 2019, Sisense acquired Periscope Data, a cloud-based focused on SQL-based and , for an undisclosed amount reportedly exceeding $100 million. This acquisition aimed to integrate Periscope's capabilities in enabling data scientists and engineers to perform in-database directly within cloud warehouses, thereby creating a more unified that bridged traditional BI tools with advanced team workflows. The move enhanced Sisense's offerings by combining its embedded strengths with Periscope's emphasis on scalable, query-driven insights, allowing users to handle large datasets without extensive movement. Following the acquisition, Sisense completed the integration in early 2020 through a full merger, rebranding Data as Sisense for Cloud Data Teams. This rebranding incorporated Periscope's in-warehouse preparation tools, which enable direct and optimization of datasets within cloud environments like or , alongside predictive modeling features powered by integrations such as . The merger streamlined operations, merging teams and products to accelerate development of end-to-end solutions tailored for professionals. Post-2019, Sisense pursued strategic expansions into AI-driven and embedded analytics without further major acquisitions, emphasizing organic innovation in modular data products. These efforts included the development of AI-powered tools like Sisense Intelligence, launched in 2025, which embeds generative AI capabilities for contextual insights and scalable within applications. By focusing on low-code and pro-code modular components, Sisense enhanced its platform's flexibility for builders integrating into products, prioritizing genAI advancements to drive user adoption and revenue growth through internal R&D. Up to 2025, the company reported no additional significant mergers or buys, instead leveraging a 2020 round exceeding $100 million to fuel these organic expansions.

Company

Leadership and Organization

Sisense was founded in 2004 by a team that included Eldad Farkash, who served as the initial and key architect of its early technical direction, alongside co-founders Adi Azaria, Aviad Harell, Elad Israeli, and Guy Boyangu. Early leadership featured Amit Bendov as CEO until 2014, overseeing initial product development and market entry. In 2015, Amir Orad was appointed CEO, shifting the company's strategic emphasis toward embedded solutions and accelerating global expansion through subsequent funding rounds. Orad's tenure, which lasted until April 2023, positioned Sisense as a leader in AI-driven , culminating in its status. As of 2023, Ariel Katz serves as CEO, having previously held the role of Chief Product and Technology Officer where he championed the integration of AI capabilities across the platform to enhance data democratization and workflow automation. The board of directors includes prominent investors such as Teddie Wardi from , alongside representatives from , , and DFJ Growth, providing strategic oversight for innovation and scaling. The organization has evolved from a small team of approximately 10 employees in its founding year to nearly 500 by , reflecting rapid expansion driven by product innovation and market demand. experienced significant workforce reductions through multiple layoffs starting in 2022, decreasing from around 800 to approximately 600 employees by 2025. This growth supported a distributed structure with core research and development based in and primary sales and customer operations in the United States. Sisense's core values emphasize innovation in analytics technology, customer-centric product design, and fostering an inclusive workplace environment, as articulated in its official mission to empower data-driven decisions globally.

Operations and Global Reach

Sisense is headquartered in , , with its primary research and development center located in Ramat Gan, near , . The company maintains additional offices in , , and , among others, to support its distributed operations across multiple continents. These locations facilitate a global workforce of approximately 600 employees as of 2025, enabling collaboration in product development, sales, and customer support. Sisense operates on a subscription-based software-as-a-service () model, delivering () and solutions primarily to enterprises in sectors such as , healthcare, and . This approach allows clients to access scalable, cloud-hosted tools without extensive on-premises infrastructure. In the 2020s, Sisense transitioned from traditional on-premises deployments to a cloud-first , beginning with a Linux-based architecture in 2019 and rebranding integrations like Periscope Data as Sisense for Cloud Data Teams in 2020. This shift has emphasized capabilities, enabling original equipment manufacturer () partners to integrate Sisense's tools directly into their applications for seamless data insights. The company's customer base comprises over 2,000 clients worldwide, including numerous organizations that leverage Sisense for data-driven decision-making. As of 2025, Sisense continues to emphasize AI-driven innovations, incorporating features to enhance and automate insights across its platform. Under executive leadership oversight, these global expansions have strengthened Sisense's ability to serve diverse markets efficiently.

Products

Core Platform and Offerings

Sisense offers an end-to-end (BI) platform that enables data ingestion from diverse sources, advanced analysis, and interactive to deliver actionable insights. Launched publicly in 2010, the platform has evolved significantly to incorporate embedded analytics capabilities, allowing seamless integration of dashboards and reports into custom applications for enhanced user experiences. A key component is Sisense for Cloud Data Teams, introduced following the 2019 acquisition of Periscope Data and rebranded in 2020, which provides data engineers with tools to connect databases, execute SQL, , and queries, and generate shareable reports and dashboards from large datasets. This offering streamlines workflows for technical users by supporting code-based analysis and collaboration, such as integrations for report previews. In 2025, Sisense launched Sisense Intelligence, a modular -powered suite that leverages generative for data exploration, automated visualizations, trend forecasting, and explanatory insights to accelerate the creation of data products. This addition enhances the platform's ability to generate genAI-driven insights, enabling teams to build and embed intelligent more efficiently. In October 2025, Sisense released version 2025.4, which includes enhancements to the assistant, primary filters, and instant semantic publishing for improved capabilities. The core , powered by ElastiCube technology for optimized processing, supports deployment across on-premises, cloud environments like AWS and , and hybrid models to meet varying organizational needs. is structured in flexible tiers ranging from starter plans for small teams to enterprise-level custom quotes, ensuring based on count, volume, and features. Target use cases include constructing interactive dashboards for real-time decision-making and embedding into applications, empowering non-technical s with intuitive, context-aware access without requiring deep coding expertise.

Key Features and Capabilities

Sisense provides interactive dashboards that enable users to build and customize visualizations through an intuitive drag-and-drop , supporting exploration with features like dynamic filters and multi-level drill-downs to uncover insights from complex datasets. These dashboards facilitate seamless navigation and interaction, allowing teams to slice and dice data without requiring advanced technical skills, thereby enhancing decision-making efficiency across organizations. A core capability of Sisense is its embedded analytics functionality, which supports white-label integration into customer-facing applications using iFrames, Embed SDKs, and libraries to deliver branded, seamless experiences. This feature accommodates pro-code, low-code, and no-code development approaches, enabling developers and non-technical users alike to incorporate directly into products like platforms or apps for personalized user interactions. For instance, the Compose SDK allows customization of elements such as colors, fonts, and layouts to match brand identities, ensuring a cohesive end-user experience. Sisense Intelligence, introduced in a 2025 update, integrates advanced enhancements including querying through a conversational Assistant that allows users to explore data and generate visualizations via plain English prompts within dashboards. Automated insights are powered by tools like , which generates summaries of query results and highlights key trends, and , which identifies probable causes of changes. Predictive modeling capabilities include Forecast for machine learning-based trend predictions from historical data and Trend for applying statistical trendlines to visualize patterns, all accessible on the deployment without needing external keys. Collaboration is streamlined through built-in tools for sharing dashboards via links or embeds, adding comments on visualizations using widgets like BloX for team , and exporting reports in various formats for offline use or with other systems. These features promote cross-functional teamwork, particularly in cloud environments where real-time updates and ensure synchronized access to evolving . Security is a foundational aspect of Sisense's offerings, featuring (RBAC) to define granular permissions for users and segments, alongside (SSO) via OAuth and SAML for secure authentication. is protected with both at rest—using OS-based and shared storage defaults—and in transit, complying with standards like GDPR, SOC 2 Type II, ISO 27001, and HIPAA. Additional measures include management and audit logs to track access and maintain compliance in deployments. Sisense also connects to over 400 sources for broad integration, supporting diverse analytics needs without specialized engineering.

Technology

Architecture and Infrastructure

Sisense's architecture supports both single-server and distributed deployments to accommodate varying organizational needs. In a single-server setup, all core components operate on one machine, making it suitable for proof-of-concept environments or smaller integrations. Distributed deployments, however, span multiple for enhanced performance and reliability, with configurations such as one application node paired with dedicated query and build nodes, or scaled models featuring multiple application and query nodes alongside build nodes. The Sisense Server handles overall , the Web Server delivers the including dashboards and administrative tools, and the ElastiCube Manager facilitates and cube creation. The platform embraces a hybrid cloud architecture, enabling deployments on major providers like (AWS), , and (GCP). Sisense is containerized using , with orchestration managed through , allowing for flexible provisioning on services such as Amazon EKS, Azure AKS, and Google GKE. This setup supports on-premises installations alongside cloud-hosted options, where Sisense-managed services run on AWS infrastructure with across regions. The ElastiCube technology plays a key role in processing imported data into optimized models for analysis. Scalability is achieved through horizontal scaling in multi-node environments, incorporating load balancing to manage high traffic and concurrent users. The system efficiently allocates resources via key components including the for handling queries against data models, the Query Engine for processing requests, and a Metadata Layer stored in an application database for managing configurations and user data. This design supports handling large-scale datasets comprising billions of records, with recommendations for high-memory setups (up to 512GB and 32 cores) in demanding scenarios. Post-2020, Sisense evolved toward a microservices-based with the introduction of its Linux edition, transitioning from traditional IIS to for greater modularity, particularly in embedded analytics use cases. This shift leverages and service isolation (e.g., Sisense.Identity and Sisense.Galaxy modules) to improve deployment flexibility and maintenance in cloud-native environments.

Data Processing and Analytics Engine

Sisense's ElastiCube technology serves as the core of its engine, functioning as a columnar database that uses memory-mapped files on disk for , enabling efficient loading and of during queries to reduce compared to traditional row-based databases. This technology employs a columnar and query that leverages In-Chip to accelerate handling, enabling the and of billions of records while supporting computations for complex joins and aggregations. By loading into a compressed, indexed format in for , ElastiCube reduces compared to traditional row-based databases, often delivering query results in seconds for datasets comprising hundreds of millions of rows. Data integration in Sisense is facilitated through a robust set of native connectors supporting over 400 connectors, including SQL databases like and , NoSQL systems, cloud warehouses such as and , and APIs from web applications. These connectors enable both ETL () and ELT pipelines for , as well as live connections that query data in real-time without full ingestion into ElastiCube sets. This flexibility allows users to unify disparate data sources into a single model, with automated workflows handling transformations and mapping to prepare data for analytics. The engine builds on ElastiCube by supporting advanced scripting and computation, including SQL for query generation, and for statistical analysis and custom functions, where results from SQL queries can be directly fed into scripts for deeper processing. It incorporates and capabilities for tasks such as , predictive forecasting, and , enabling automated insights without extensive coding. Performance is further optimized through techniques like field indexing to speed up , multi-level caching to store frequently accessed results, and advanced algorithms that minimize I/O overhead, consistently achieving sub-second to few-second query times even on massive datasets. In 2025, Sisense introduced updates enhancing the engine with semantic enrichment powered by generative , which automatically generates descriptions, tags, and relationships for data models to improve discoverability and preparation efficiency. This includes machine learning-driven updates to the , such as enriching column metadata and enabling automated , reducing manual preparation time for workflows. These features integrate seamlessly with visualizations, allowing AI-enriched models to power dynamic, context-aware reports.

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