San Francisco, CA – Redbird, a pioneering technology company, has officially launched its AI chat platform designed to address the challenges enterprise organizations face in utilizing chat-based approaches for business intelligence (BI). While consumer-focused tools like ChatGPT have made strides in offering general information, enterprises have struggled to apply similar technologies to their complex data analytics needs in a way that is accurate, secure, and tailored to their unique environments.
Bridging the Gap in Self-Serve Analytics
Redbird’s AI platform is filling a crucial gap by introducing AI agents that can perform advanced data analytics seamlessly on top of an organization’s existing data ecosystem. Users can interact with these AI agents in natural language without needing technical expertise, thus enabling a level of self-service analytics that legacy dashboarding tools like Tableau, Looker, and PowerBI have not achieved.
“For decades, the promise of true self-serve analytics has remained unfulfilled,” stated Erin Tavgac, Co-Founder and CEO of Redbird. “Organizations have instead faced complex data pipelines and dashboards that demand technical skills. We have dedicated substantial resources into integrating the power of large language models (LLMs) with Redbird’s comprehensive analytical toolkit, creating AI agents that enable conversational BI based on an organization’s own data.”
Advanced AI Agents for Specialized Tasks
Redbird’s platform utilizes proprietary AI agents trained to carry out specific analytical tasks akin to those performed by specialized human resources. Examples of these tasks include data collection, data engineering, SQL analysis, reporting, and domain-specific analytics. These AI agents can orchestrate and execute multi-step analytical tasks, effectively responding to user inquiries.
An added layer of customization is provided through an admin interface, where domain experts within an organization can input business logic, definitions, data ontologies, and existing assets such as presentations or documents. This contextual information allows the AI to deliver accurate and relevant results.
Ensuring Security and Infrastructure Readiness
Recognizing the infrastructure and security challenges that come with implementing AI in enterprises, Redbird offers turnkey on-premises deployments. These solutions allow organizations to run LLMs within their own cloud environments, ensuring that all data remains securely contained within their AI ecosystem and is never used to train LLMs for other enterprises.
Redbird’s Growing Impact in 2024
As 2023 progressed, many enterprises observed advancements in LLM technology from a distance, unsure how to effectively incorporate it. However, as they begin testing various approaches in 2024, there has been a marked shift toward allocating budgets for AI solutions that deliver real value. Many in-house efforts have proven costly and ineffective due to the challenges of integrating LLM technology with complex enterprise data ecosystems.
In contrast, Redbird’s AI solution is rapidly gaining traction among some of the largest enterprise brands, providing a viable alternative to both complicated internal builds and superficial third-party products like Microsoft Copilot.
Since raising its seed funding in 2022, Redbird has seen significant growth, increasing its customer base sevenfold and tripling its workforce. The company is now collaborating with eight of the Fortune 50 brands and is onboarding several large government organizations in the U.S.
Founded by Erin and Deren Tavgac, data analytics and AI experts with extensive experience in large enterprises, Redbird is poised to make a significant impact across diverse verticals as it continues to develop its innovative AI platform.
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