Recent advancements in AI and large language models (LLMs) have transformed the technology landscape, yet businesses still face challenges in utilizing chat-based solutions for effective business intelligence (BI).
While generative AI tools like ChatGPT have proven capable of surface-level tasks, they often fall short in applications that require the deeper data analytics needed within the complex data ecosystems of enterprises.
To fill this void, Redbird Software, a New York-based startup, has introduced a new generative AI platform named Redbird. This new GenAI platform uses specialized AI agents to assist enterprises in managing various tasks across the data analytics value chain. This includes the generation of actionable insights from reporting, and streamlining various processes from data collection to data engineering.
Redbird is designed to perform advanced data analytics by securely integrating with an organization’s data ecosystem. Users can engage with the platform using natural language prompts, eliminating the need for technical expertise. Redbird claims this “self-service analytics” offer a more intuitive experience compared to legacy dashboarding systems such as PowerBI, Looker, and Tableau.
The AI platform uses proprietary agents to perform specialized analytics tasks such as SQL analysis, data science, and reporting. The agents can be set up to execute multi-step tasks and are supported by an admin layer for inputting business logic, adding reporting blueprints, or enhancing contextual understanding.
Redbird also provides turnkey on-premise deployments, enabling organizations to run large language models (LLMs) securely within their own cloud environments, ensuring that data stays protected and confidential.
“For the past several decades the promise of truly self-serve analytics has fallen short for organizations, 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 organization’s data.”
Redbird offers a broad array of connectors, including integrations with Databricks and Salesforce. These connectors streamline the process of automating data extraction into the platform, enabling seamless data processing for analysis.
(VideoFlow/Shutterstock)
Once the raw data is streamed into the platform, users can identify and remove errors, such as duplicate records. They can also standardize the dataset into a consistent format, making it easier to analyze and process across different tools.
The launch of Redbird comes almost two years after the startup secured a $7.6M seed round. Since then, the startup claims to have tripled its team size, developed an extensive AI ecosystem and increased its user count sevenfold. Redbird now serves eight of the Fortune 50 brands in its customer base, and the startup revealed that is currently onboarding several major U.S. government agencies to its platform.
Redbird’s introduction marks a significant step toward its goal of democratizing data analytics. Looking ahead, the startup is planning to roll out more advanced AI agents that will boost business intelligence capabilities and automate tasks based on analytical insights, like generating invoices or placing supply orders.
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