Starburst, a leading enterprise intelligence platform, today announced its AI Data Assistant (AIDA), a new capability that helps organizations move from static reporting to faster, more context-aware decision-making. With AIDA, users can explore and analyze trusted enterprise data using natural language, making it easier to turn questions into actionable insight. Teams wait months for the creation of dashboards, export results into spreadsheets, and still question whether the numbers can be trusted.
Starburst launches AI Data Assistant (AIDA) enabling natural language exploration of trusted enterprise data.
AIDA uses a ReAct (reason-act-observe) framework for true analytical reasoning beyond query generation.
Persona-based outputs tailor responses for data practitioners or business leaders.
Flexible LLM support includes Anthropic, OpenAI, and AWS Bedrock without vendor lock-in.
Coming Q2: AIDA Studio for extensibility, MCP Client for Slack/Jira/GitHub integration, and configurable Guardrails.
AIDA helps recover lost revenue, prevent churn, and accelerate fraud investigations.
"Most companies are still approaching AI the wrong way, focusing on models instead of the data those models depend on," said Justin Borgman, Co-founder and CEO of Starburst. "The real challenge is applying AI to business decisions without moving data or compromising governance. Starburst's AI Data Assistant is built to solve that by providing access to trusted, distributed data from across the enterprise."
Advanced Reasoning Capabilities: AIDA leverages a ReAct (reason-act-observe) framework to move beyond query generation into true analytical reasoning, combining live data sampling and metadata analysis to reach a well-grounded answer. The result is an assistant that reasons through problems like an analyst, not just a text-to-query translator.
Persona-Based Outputs: AIDA tailors responses based on user role, delivering detailed technical explanations for data practitioners and concise, decision-ready summaries for business leaders.
White Labeling: Organizations can apply their own branding to AIDA to create a seamless internal analytics experience without additional development. Available today in Starburst Enterprise Platform (SEP).
Flexible LLM Support: Within SEP, AIDA supports multiple LLMs, including models from Anthropic, OpenAI, and AWS Bedrock, enabling enterprises to choose the model that best fits their technical, security, and cost requirements without vendor lock-in.
Starburst plans to release the following:
AIDA Studio: An extensibility layer that enables integration with external systems, incorporation of unstructured business context, and creation of custom skills to orchestrate workflows across tools like Slack, Jira, and Google Workspace.
AIDA MCP Client: The AIDA MCP Client Layer gives AIDA the ability to interact with and pull context from enterprise applications such as Slack, Jira, and GitHub using the open Model Context Protocol (MCP). Users can add context to inform AIDA's outputs, and even use AIDA more broadly as an automation hub for important enterprise tasks.
Guardrails: A configurable governance layer that controls AI interactions and outputs, enforcing policies beyond underlying data access. Organizations can restrict sensitive topics and prevent exposure of personal data, ensuring safe and compliant AI usage.
Unlike traditional approaches that depend on centralized data architectures built for business intelligence, Starburst enables AI to operate directly on distributed data across lakes, warehouses, cloud object storage, and operational systems. While competing approaches often require data to be moved into a vendor-controlled environment before AI can act on it, Starburst brings AI to the data wherever it resides without lock-in. By applying governance, definitions, and access controls consistently across data sources, Starburst provides the federated context layer required for enterprise AI connecting distributed data, business meaning, and policy into a single AI-ready foundation.
"As enterprises seek to democratize analytics with agentic AI, they need governed access to distributed datasets," said Kevin Petrie, Vice President of Research at BARC US. "Starburst meets this requirement and goes further to enable intent- and persona-specific reasoning on federated inputs. This helps diverse stakeholders make smarter decisions in the context of the business."
Recover lost revenue by identifying billing discrepancies across contracts, usage, and invoicing data, quantifying the impact, and triggering corrective actions, helping reduce the 1-3% of revenue often lost to leakage.
Prevent customer churn by detecting early warning signs from usage, support, and sentiment data, generating customer health insights, and prompting timely interventions, turning at-risk renewals into retention opportunities.
Accelerate fraud and compliance investigations by surfacing suspicious activity across transactions and customer data, enriching it with full context, and automating case creation — reducing manual investigation time while improving accuracy.
About Starburst
Starburst delivers enterprise intelligence at scale. Our platform provides agents with secure access to all of a company's data across on-premises systems, multiple clouds, and hybrid environments without the traditional consolidation that leaves critical information behind. Starburst enables federated access to all of an organization's distributed data allowing AI platforms the complete enterprise context they need to operate at scale, removing the barriers that prevent pilot projects from entering into production. Business leaders get faster time to actionable insights, governed collaboration, and greater confidence in decisions based on trustworthy, complete data. Built on open standards with Trino and Apache Iceberg, Starburst integrates with existing technologies and avoids vendor lock-in. That's why leading enterprises in more than 60 countries — including Comcast, Citigroup, and four of the top five global banks — trust Starburst to fuel enterprise intelligence.
