New York-based analytics company Redbird has announced the launch of a groundbreaking platform that could reshape the way enterprises approach business intelligence. The innovative chat system leverages AI agents, designed to handle 90% of the analytics value chain—from data collection and engineering to generating actionable insights. This new system promises to radically streamline the process, allowing enterprise users to obtain critical business insights almost in real-time, using nothing more than a natural language prompt.
According to Redbird’s CEO and co-founder, Erin Tavgac, the new platform represents a major leap towards truly self-serve analytics. For years, organisations have struggled with complex, technical data pipelines and cumbersome dashboards that often required advanced skills to operate. Redbird’s new AI agents aim to eliminate those hurdles, empowering users with easy, conversational business intelligence (BI).
“For decades, the promise of self-service analytics has fallen short. But with the fusion of large language models (LLMs) and Redbird’s comprehensive analytics toolkit, we’re bringing conversational BI to life. It’s a system that can truly operate on an organisation’s data,” Tavgac said.
The Dawn of AI Agents
While AI agents are a relatively new development, Redbird itself has been pioneering in the analytics space since its launch in 2018, originally under the name Cube Analytics. The company has long offered no-code tools designed to automate and unify analytics tasks. However, this new platform, equipped with AI agents, takes things a step further by introducing a conversational interface capable of executing complex, multi-step analytics tasks with ease.
Admins setting up the system choose a base language model, such as GPT or Llama, and integrate their company’s proprietary data, including business logic and reporting blueprints. The AI agents then go to work, using this data to execute specific analytics tasks in response to user queries.
“User prompts are routed to Redbird’s AI agents, each specialising in different areas such as data engineering, PowerPoint reporting, or campaign execution. The agents work together to orchestrate the overall task, pulling data from more than 100 sources, including Snowflake and Databricks,” Tavgac explained.
Once the task is completed, the platform not only provides a text response but also delivers the necessary outputs—whether it’s a PowerPoint presentation, an Excel report, or real-time updates via email or Slack.
Beyond Text-to-SQL
Redbird’s announcement comes at a time when many enterprises are looking to enhance their data efforts with AI-driven solutions. While tools like text-to-SQL, already adopted by companies like Dremio and Snowflake, have automated portions of the analytics process, Redbird’s AI agents go much further. The system is capable of handling the full analytics pipeline, from data collection and wrangling to reporting and taking real-time actions based on the insights produced.
For companies still hesitant about fully relying on AI, Redbird has retained its original no-code, drag-and-drop interface as a secondary option. This allows users to audit and inspect workflows to ensure accuracy, while also offering transparency into how the AI agents orchestrate each task.
“So far, existing AI solutions have only automated a fraction of BI tasks, mainly around SQL querying. Redbird solves that, but we’re also automating the much more challenging aspects of BI workflows,” said Tavgac.
Fortune 50 Brands on Board
Redbird’s platform has already caught the attention of major global enterprises. Eight of the Fortune 50 brands have adopted the AI agent system, alongside over 30 mid-to-large-sized companies. Among their early adopters are major names such as Mondelez International, USA Today, Bobcat Company, and Johnson & Johnson.
The company is offering its platform via a SaaS model with usage-based licensing fees. While Redbird has reportedly generated seven-figure revenue, specifics have not been disclosed.
As Redbird pushes forward, it plans to introduce even more advanced AI agents that can take deeper action based on analytical outcomes—actions like purchasing supplies or sending invoices, rather than simply reporting insights. This move marks a potential shift toward what Tavgac describes as a “Large Action Model,” bringing AI-powered decision-making into everyday business operations.
With its sights set on expanding into even more enterprises and adding further functionality, Redbird is positioning itself at the forefront of the AI analytics revolution—one where natural language commands may soon handle the heavy lifting of business intelligence.
