Starburst has unveiled its new AI Data Assistant (AIDA) as part of its enterprise intelligence offering, designed to enhance decision-making by shifting from conventional, static reporting to more dynamic, context-aware insights. AIDA empowers organizations to explore and analyze verified enterprise data through natural language queries, thereby facilitating the transformation of inquiries into actionable insights.
The traditional data processing approach often involves long waits for dashboard creation, manual data export into spreadsheets, and ongoing skepticism about data accuracy. These inefficiencies hinder the ability to make timely data-informed decisions. AIDA addresses these issues by offering on-demand access to reliable enterprise data, steering organizations toward quicker and more informed decision-making processes.
Features of AIDA
AIDA distinguishes itself with advanced reasoning capabilities by utilizing a ReAct framework—reasoning, acting, and observing—to elevate analytical reasoning. It combines live data sampling and metadata analysis to provide well-grounded answers, akin to the work of an experienced analyst rather than merely translating text into queries. Moreover, AIDA adapts its responses according to user roles, offering detailed technical explanations for data professionals and concise summaries for business executives.
Organizations can also benefit from white labeling by integrating their branding into AIDA
Organizations can also benefit from white labeling by integrating their branding into AIDA, which enables a cohesive internal analytics experience without additional development. Furthermore, AIDA supports multiple large language models (LLMs) from providers like Anthropic, OpenAI, and AWS Bedrock, giving businesses the flexibility to choose models that align with their specific technical, security, and budgetary needs.
Upcoming Capabilities and Enhancements
Starburst is set to expand AIDA's capabilities in the second quarter with the introduction of AIDA Studio, an extensibility layer that facilitates integration with external systems, unstructured business context incorporation, and workflow orchestration across platforms like Slack, Jira, and Google Workspace.
The upcoming AIDA MCP Client will enable interaction with enterprise applications, drawing context from tools like Slack and Jira, and allowing broader use as an automation hub for critical business tasks. Furthermore, guardrails offer a governance layer to manage AI interactions and outputs, ensuring adherence to policies and safeguarding against sensitive data exposure.
Revolutionizing AI in Enterprise Environments
Starburst enables AI to function directly on distributed data residing in data lakes
According to Justin Borgman, Co-founder and CEO of Starburst, the focus should be on the underlying data rather than just AI models. AIDA aims to enhance business decision-making by providing access to distributed, trustworthy data without compromising governance or necessitating data relocation.
By leveraging a federated context layer across diverse data sources, Starburst enables AI to function directly on distributed data residing in data lakes, warehouses, cloud storages, and operational systems, eliminating the need for centralized architecture and potential vendor lock-in. This comprehensive approach fosters informed decision-making while maintaining data integrity and security.
Benefits in Revenue Protection and Risk Management
Enterprises stand to benefit significantly, including revenue recovery through billing discrepancy identification, quantifying impacts, and initiating corrective actions to reduce typical revenue leakage of 1–3%. Detection of early warning signs of customer churn is also improved through comprehensive analysis of usage and sentiment data, helping convert at-risk renewals into retention opportunities.
Moreover, AIDA enhances fraud and compliance investigations by identifying suspicious activities in transactional and customer records. By enriching these investigations with full context and automating case creation, it reduces manual intervention time while increasing accuracy.
Starburst, a pioneer enterprise intelligence platform, announces 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 the results into spreadsheets for further analysis, and still question whether the numbers can be trusted. That gap makes it difficult to act on data when it matters most.
Trusted enterprise data
Users, applications, and AI systems need governed access to data across the business to act with speed and context. Yet for years, centralization has been treated as transformation, even in enterprises where data is spread across clouds, platforms, and operational systems.
With AIDA, organizations can move beyond static reporting and give users governed, on-demand access to trusted enterprise data, enabling faster, more context-aware decisions.
What’s new in AIDA
- 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.
Important enterprise tasks
Coming in Q2, 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, 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.
Centralized data architectures
"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."
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.
AI connecting distributed data
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. AIDA is the interface. The Starburst platform is what enables it to operate across the enterprise.
“As enterprises seek to democratise 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.”
Identifying billing discrepancies
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.
