Sisense unveils new suite of AI-powered capabilities
Featuring a natural language interface and autonomous capabilities to augment human analysis, the vendor's toolkit simplifies developing and embedding advanced applications.
Sisense on Wednesday unveiled a new suite of generative AI-powered analytics capabilities that can be embedded in the workflows of users to simplify and speed insight generation.
Sisense Intelligence, part of the vendor's Compose SDK for Fusion platform, features Assistant, a natural language interface in preview that enables technical and non-technical users to ingest and model data, create analytics tools and embed them into work applications. In addition, Sisense Intelligence includes a set of generative AI (GenAI) capabilities, now generally available, that can be included in any analytics application to augment human analysis.
It's highly significant for Sisense users because it will directly impact and simplify how folks -- and eventually other systems -- get tasks done with data.
Mike LeoneAnalyst, Enterprise Strategy Group
Sisense is not the first vendor to introduce GenAI capabilities that enable customers to easily develop and embed applications. For example, Domo and Strategy (formerly MicroStrategy) both enable users to develop and embed GenAI tools.
In any case, the tools are valuable for the vendor's customers, given that they address the disconnect between data analysis and taking action by embedding AI-infused data in user workflows, according to Mike Leone, an analyst at Enterprise Strategy Group, now part of Omdia.
"It's highly significant for Sisense users because it will directly impact and simplify how folks -- and eventually other systems -- get tasks done with data," he said.
Based in New York City, Sisense is a longtime analytics vendor whose platform enables users to develop and embed data products to simplify analysis.
New capabilities
Many enterprises have boosted their investments in AI development since OpenAI's November 2022 launch of ChatGPT marked a significant improvement in GenAI technology. Given that data provides the intelligence in AI, data management and analytics vendors have responded by building environments that simplify AI development and deployment for their customers.
Compose SDK for Fusion is a platform that enables customers to develop customized applications -- including GenAI -- with more than 500 application programming interfaces (APIs) to choose from and embed those applications within end-user workflows.
Sisense Intelligence builds on the capabilities of Compose SDK for Fusion by using GenAI to help users more easily create embeddable analytics tools and analyze data. As a result, Sisense Intelligence is a significant set of tools for the vendor's users, according to David Menninger, an analyst at ISG Software Research.
"Sisense customers will consider Sisense Intelligence a significant addition or enhancement to the product," he said.
Assistant is an AI-powered interface for building GenAI-infused analytics tools. It enables users to build applications such as dashboards using natural language rather than code. APIs within Compose SDK for Fusion then allow users to easily embed the analytics tools in end-user workflows.
Meanwhile, GenAI capabilities that can be built into the analytics tools include the following:
Narrative to automatically generate summaries on dashboards that augment data interpretation to improve data literacy.
Explanation to identify key drivers behind data changes to help users understand why something is happening.
Trend to detect meaningful patterns and outliers in data.
Sisense Intelligence is largely the same as GenAI tools being released by competing analytics vendors, according to Menninger. However, Sisense is part of a smaller group enabling users to embed GenAI capabilities.
"These new capabilities are becoming standard features of most analytics products, [but] one area where Sisense may be distinguishing themselves is by making these features available in embedded analytics using their SDK," he said.
Whether unique or not, given that natural language processing has evolved significantly since Sisense first introduced NLP capabilities in 2020, providing users with a natural language interface for development and other conversational capabilities is valuable, he continued.
"Beyond that, the explanation and automated forecasting capabilities will help provide insights that would previously have required a fair amount of work," Menninger said.
Leone, likewise, noted that while the AI capabilities included in Sisense Intelligence are similar to those offered by fellow analytics vendors, making them embeddable sets Sisense apart.
"Instead of just enhancing dashboards, which is what we're hearing from all analytics vendors, Sisense is … letting developers weave smart, data-driven experiences directly into the apps they already use," he said. "It's a smart play that moves customers beyond simply making more engaging dashboards and reports."
The longstanding disconnect between data and decision-making provided the impetus for developing Sisense Intelligence, according to Yael Lev, the vendor's AI and Data Science director.
More than three-quarters of all organizations make business decisions without consulting data because data is too difficult to access, she noted, citing a recent Sisense survey of more than 500 respondents. Embedding AI-powered analytics in user workflows aims to eradicate the disconnect between data and decision-making.
"We saw businesses struggling with traditional BI tools that required leaving their workflow to consult dashboards," Lev said. "This inspired us to build a platform that transforms how organizations turn data into business-critical insights."
Looking ahead
With Sisense Intelligence now part of Compose SDK for Fusion, Sisense will continue to make AI a focal point of its roadmap, according to Lev.
The vendor plans to continue investing in its semantic layer to power accurate, context-aware AI and simplify data preparation, she said. In addition, Sisense plans to add more agentic AI features in conjunction with improved GenAI capabilities.
Focusing on autonomous AI capabilities is wise, according to Leone.
"They should continue to lean into making their AI more proactive and prescriptive, meaning it doesn't just show data but suggests actions and integrates deeper into workflows," he said. "By focusing on actionable intelligence, alongside trust areas like governance and explainability, customers should be able to see value faster."
Menninger, meanwhile, noted that while Sisense Intelligence makes it easier to do analysis, it doesn't provide insight into what to do next. Adding planning capabilities and more agentic AI could be the next step for Sisense so users can better understand what action to take based on analysis.
"I expect we'll see more of these types of capabilities from Sisense and others in the future," Menninger said.
Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than 25 years of experience. He covers analytics and data management.
