ThoughtSpot is betting big on AI-powered assistance, expanding its “Spotter” suite with specialized agents that promise to automate and connect every stage of the data analytics workflow. The goal is ambitious: to provide an AI companion for every role within the data organization, handling the grunt work so humans can concentrate on strategy and interpretation.
The new agents, designed to work as a team, tackle specific pain points in the analytics process. Think of them as the Avengers of Business Intelligence, each with a unique superpower:
SpotterViz: The Dashboard Dynamo
SpotterViz tackles the bane of every data analyst’s existence: dashboard creation. This “liveboard” agent uses natural language to automate the design, layout, styling, and publishing of dashboards. Less time wrestling with formatting, more time uncovering actionable insights. The promise? Analysts spend less time building and more time understanding.
SpotterModel: The Data Architect
Data modeling is the foundation upon which all analytics are built, and SpotterModel aims to streamline this crucial process. This agent assists data engineers in building reusable semantic models using natural language prompts. It automates data table selection, schema generation, and the creation of joins, all while aligning with core business logic. With native integrations into Snowflake, Databricks, and dbt Labs, SpotterModel seeks to become the linchpin of modern data engineering workflows.
SpotterCode: The Embedding Expert
Want to weave the power of ThoughtSpot directly into your applications? SpotterCode is your AI-assisted coding companion. This agent accelerates the development of embedded analytics by generating code tailored to popular IDEs like Cursor, Claude Code, Github Copilot, and Microsoft VSCode. It understands the context of a developer’s project and generates code that leverages the full potential of ThoughtSpot’s SDK. This means faster development cycles and more seamless integration of analytics into everyday workflows.
The core intelligence engine, Spotter 3, receives a significant upgrade with the ability to blend structured and unstructured data. This allows analysts to tap into a broader range of data sources, including applications like Slack and Salesforce. Imagine the possibilities of combining traditional metrics with real-time customer sentiment analysis from social media – that’s the kind of power Spotter 3 unlocks. Moreover, Spotter 3 can now assess the quality of its own answers and run additional analyses until it arrives at the most accurate result.
“With our team of agents, we are delivering the industry’s first unified platform that augments every role—analysts, data engineers, developers, and business users—with an intelligent agent that handles the manual work,” said Francois Lopitaux, ThoughtSpot senior vice president of product management.
ThoughtSpot recognizes the importance of its partner ecosystem. According to Lopitaux, system integrators can leverage the new agentic tools to develop analytical applications for clients more quickly than before, while ISV partners can use the agents to build more complex solutions. And Spotter 3’s ability to access unstructured data allows those applications to interact with a greater range of systems.
Spotter 3 and SpotterCode are available now, with SpotterViz and SpotterModel rolling out over the next few months. As ThoughtSpot positions its “Spotter” AI agent technology as the future of data analytics, as reported by CRN, the question becomes: will this suite of AI assistants truly liberate data teams, or simply add another layer of complexity to an already intricate landscape? Only time, and real-world implementation, will tell.