Redbird introduces new conversational AI for enterprise BI

Redbird has launched a new conversational AI platform designed to make enterprise business intelligence tasks as easy as performing a Google search.

The company, based in New York, aims to disrupt traditional methods of data analytics with a chat-based system powered by AI agents.

Traditionally, enterprise organisations have faced challenges in utilising chat-based approaches for business intelligence in a manner that is accurate, secure, and tailored to their specific needs. Tools such as ChatGPT have demonstrated potential for general information tasks but have not effectively bridged the gap when it comes to the complex data analytics required by enterprises.

Redbird's new AI chat platform introduces AI agents capable of carrying out advanced data analytics, which securely integrate with an organisation's data ecosystem. These AI agents allow users to engage in natural language conversations without needing any technical skills, thereby enabling self-serve analytics. "For the past several decades, the promise of truly self-serve analytics has fallen short for organisations, with the reality instead being complex data pipelines, dashboards, and shadow analytics that require technical skills to execute," said Erin Tavgac, Co-Founder and CEO of Redbird. "We have invested significant R&D into fusing the power of LLMs with Redbird's robust end-to-end analytical toolkit in the form of AI agents that enable users to finally achieve self-serve, conversational BI that runs on their organisation's data."

The firm's AI platform employs proprietary AI agents trained to execute specific analytical tasks traditionally performed by specialised human resources. These tasks include data collection, data engineering, SQL analysis, data science, reporting, and domain-specific data analytics. The platform also features an admin layer where domain experts within an organisation can load business logic, definitions, data ontologies, and existing assets such as presentations or documents that the AI refers to for context.

To address infrastructure and security concerns, Redbird offers turnkey on-premises deployments that enable enterprises to run LLMs within contained environments in their own cloud systems. This ensures that all enterprise data remains securely contained within the enterprise's AI ecosystem and is not used to train LLMs for other organisations.

In recent years, enterprises have closely monitored advancements in LLM technology, exploring its potential within their operations. However, efforts to develop in-house solutions have often proven costly and ineffective due to the complexities involved. Third-party AI products like Microsoft Copilot have also fallen short, providing only surface-level assistance. Redbird's AI product offers an alternative, gaining traction among large enterprises as a viable solution to these challenges.

Since its seed funding in 2022, Redbird has seen its customer base grow sevenfold, tripled its team size, and developed an extensive AI ecosystem built on its core data analytics automation platform. The company now works with eight of the Fortune 50 brands and is in the process of onboarding significant government organisations in the US.

Founded by Erin Tavgac and Deren Tavgac, who bring substantial data analytics and AI expertise from their experience with major global brands, Redbird has expanded rapidly. The team has included key AI engineering hires to further accelerate the development of their AI product. Currently, Redbird's technology is used by numerous enterprise customers across various sectors.

Redbird seeks to unlock the potential of conversational business intelligence for enterprises, marking what it sees as a significant step forward in its mission to democratise data analytics.