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Recent advances in AI and large language models (LLM) have transformed the technology landscape, but businesses still face challenges in using chat-based solutions for effective business intelligence (BI).
Although generative AI tools such as ChatGPT have proven capable of performing surface-level tasks, they are often not up to the task of applications that require deeper data analyzes needed within business ecosystems. complex business data.
To fill this void, Redbird Software, a New York-based startup, introduced a new generative AI platform named Redbird. This new GenAI platform uses specialized AI agents to help businesses manage various tasks across the data analytics value chain. This includes generating actionable insights from reports and streamlining various processes, from data collection to data engineering.
Redbird is designed to perform advanced data analytics by integrating securely into an organization’s data ecosystem. Users can interact with the platform using natural language prompts, eliminating the need for technical expertise. Redbird claims that these “self-service analytics” provide a more intuitive experience compared to existing dashboard 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. Agents can be configured to execute multi-step tasks and are supported by an administration layer to capture business logic, add reporting plans, or improve contextual understanding.
Redbird also offers turnkey on-premises deployments, allowing organizations to run extended language models (LLMs) securely in their own cloud environments, ensuring data protection and privacy.
“Over the past few decades, the promise of truly self-service analytics has fallen short for organizations, with the reality instead being complex data pipelines, dashboards, and phantom analytics that require technical skills to execute,” said Erin Tavgac, co-founder and CEO of Redbird.
“We have invested heavily in R&D to merge the power of LLMs with Redbird’s robust end-to-end analytics toolkit in the form of AI agents that enable users to finally achieve conversational BI in self-service that runs on their organization’s data.
Redbird offers a wide range of connectors, including integrations with Databricks and Salesforce. These connectors streamline the process of automating data extraction into the platform, enabling seamless processing of data for analysis.
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Once raw data is released to 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.
Redbird launch comes nearly two years after startup obtained a funding round of $7.6 million. Since then, the startup claims to have tripled the size of its team, developed a vast AI ecosystem and increased the number of users sevenfold. Redbird now serves eight of the Fortune 50 brands among its customer base, and the startup revealed that it is currently onboarding several major U.S. government agencies onto its platform.
The introduction of Redbird marks an important step toward its goal of democratizing data analysis. Looking ahead, the startup plans to deploy more advanced AI agents that will boost business intelligence capabilities and automate tasks based on analytical insights, like generating invoices or placing orders for supplies.
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