Rasgo Introduces AI-orchestrated Analytics

Rasgo-Introduces-AI-orchestrated-Analytics

Brings the Intelligent Reasoning power of GPT to the Enterprise Data Warehouse, reducing time spent creating data products by 80%

Rasgo introduced Rasgo AI, an AI-orchestrated self-service analytics platform bringing the power of GPT to the Enterprise Data Warehouse (EDW) in a secure and trusted manner. Rasgo AI harnesses the power of GPT to revolutionise workflows for data teams and knowledge workers, removing friction and accelerating the path to continuous, accurate insights and recommended best actions.

“The integration of Rasgo into our data ecosystem has made our teams and business professionals more efficient and self-sufficient,” said Pedro Soto, Director of Enterprise Data at HD Supply. “It has lowered the barrier to exploit our data assets and shifted the way that we think about interacting with data. Before Rasgo AI, our teams were stuck using tools designed for a different time, resulting in painful back-and-forth between stakeholders and teams. Now they are empowered and generate insights faster than ever.”

While the GPT hype cycle has spurred many companies to launch GPT integrations and ChatGPT plug-ins, many are merely bringing the natural language chat interface to existing products. Rasgo AI is highly differentiated because it leverages GPT for Intelligent Reasoning to think and act like a business analyst. This is significant because talented knowledge workers are entangled in a tedious cycle of low-value tasks, often taking weeks or months to answer a single question from data. This disrupts decision-making and underutilises the true potential of an organisation’s high-value personnel. By offloading low-value tasks to AI, Rasgo empowers knowledge workers to focus on decision-making and driving enterprise value.

“The largest impediment to self-serve analytics is that existing tools are incapable of providing knowledge workers with data insights without intervention from the data team,” said Patrick Dougherty, Co-founder & CTO, Rasgo. “To address this, we’ve employed GPT-4 to perform complex reasoning tasks with dynamic objectives. With GPT-4, Rasgo AI is the first platform to deliver context-rich insights, democratizing intelligence, not just the data, and transforming business users into intelligence providers. We’re using AI to change knowledge work forever.”

Many legacy self-service analytics vendors talk about proactive insights. This usually means surfacing a few anomalies, but generative insights must create lasting business value within an organisation. By orchestrating GPT 4-enabled AI agents that can efficiently reason through tasks, strategise based on rewards, break down objectives into tactics, augment them as needed to reach an end goal, and more, Rasgo AI acts like an army of knowledge workers that proactively identify key performance and risk drivers to fuel business success. This reduces the time spent creating knowledge products by 80%. Additionally, these autonomous agents generate a semantic embedding of the EDW metadata, which is then used to teach GPT-4 about the data without it ever leaving the enterprise’s control. And with Microsoft as Rasgo’s AI API provider, it has direct ties to Microsoft’s security framework, meaning organisations can feel confident in the security standards behind the AI.

“Executives, from the CEO to the CISO, are feeling immense pressure from boardrooms and stakeholders to leverage GPT for their business to keep up with the competition. As the AI arms race heats up, many are giving close consideration to data privacy and security concerns. Black box AI can lead to disastrous outcomes and won’t cut it in the generative AI era. It’s vital that enterprises take a different approach to bringing generative AI to their business in a manner that is safe and trusted for employees, customers, and shareholders,” said Jared Parker, Co-founder & CEO, Rasgo. “Rasgo AI was built with trust and safety at the forefront by ensuring raw data never leaves the EDW, logging every AI-enabled interaction so that it’s easily discoverable for transparency and compliance, and maintaining a rich semantic layer that places guardrails around the LLM for data governance. This empowers our customers to move significantly faster than their competitors without sacrificing privacy and with a high degree of protection against AI hallucinations and data inconsistencies.”

With Rasgo, the potential for generating strategic analytical products is endless. Encouraging collaboration with and facilitating seamless interaction between knowledge workers and GPT-based agents will ensure the success of AI integrations and lead to more effective outcomes at scale.