Redbird unveils conversational AI platform while simplifying enterprise business intelligence

The New York-based firm Redbird is poised to revolutionize enterprise data analytics with the launch of its AI-driven platform, which introduces a chat-based system powered by specialized AI agents. While AI and large language models (LLMs) have made significant strides in recent years, many enterprise organizations have struggled to harness chat-based approaches for business intelligence (BI) in a way that is accurate, secure, and tailored to their unique data needs. Consumer-focused tools like ChatGPT have shown promise for surface-level tasks that rely on general internet information, but they fall short when it comes to the deep data analytics required by enterprises to navigate their complex data ecosystems.

Redbird’s AI chat platform addresses this challenge by deploying AI agents specifically designed for advanced data analytics, seamlessly integrating with an organization’s existing data infrastructure. These AI agents allow users to engage in natural language conversations, enabling self-serve analytics without the need for technical expertise. This innovation fulfills the long-awaited promise of self-serve BI that traditional dashboarding tools like Tableau, Looker, and PowerBI have struggled to deliver due to their more rigid frameworks.

Redbird’s AI platform features proprietary AI agents trained to perform specialized analytical tasks that typically require human expertise. The AI agents utilize Redbird’s analytical tools to orchestrate and execute multi-step processes to deliver accurate and insightful responses to user queries. Moreover, the platform includes an admin layer where domain experts within an organization can input business logic, definitions, data ontologies, and existing assets like presentations or documents, providing the AI with the context necessary to generate precise outcomes.

Redbird also addresses the critical infrastructure and security concerns associated with enterprise AI implementations by offering turnkey on-premises deployments that enable organizations to run LLMs within their own secure cloud environments. This approach ensures that all enterprise data remains securely contained within the organization’s AI ecosystem and is not used to train LLMs for external purposes.

Throughout 2023, many enterprises observed the rapid advancements in the LLM space, questioning how the technology could be effectively utilized within their own operations. By 2024, these organizations began experimenting with different approaches and allocating budgets in search of AI solutions that truly meet their needs. However, attempts to build in-house solutions have often been costly and ineffective due to the complexities of integrating LLM technology with the unique, often messy, data ecosystems of enterprises. Similarly, third-party AI products like Microsoft Copilot have fallen short by offering more superficial assistant functionalities rather than deep, tailored analytics. Redbird’s AI platform is rapidly gaining traction among some of the largest enterprise brands as a robust alternative to both in-house development and surface-level third-party solutions.

Founded by Erin Tavgac and Deren Tavgac, seasoned data analytics and AI experts with extensive experience across the world’s largest brands, Redbird has rapidly built a team of key AI engineering talent to accelerate the development of its AI product. As Redbird brings its AI platform to market, it is poised to help enterprises unlock the full potential of conversational BI, marking a significant leap forward in its mission to democratize data analytics.