Rasgo Introduces AI
Rasgo AI acts like an army of knowledge workers to proactively identify key performance and risk drivers to fuel business success.
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Rasgo introduced Rasgo AI, an artificial intelligence-orchestrated self-service analytics platform bringing the power of GPT to the enterprise data warehouse.
By orchestrating GPT 4-enabled AI agents that can 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 to proactively identify key performance and risk drivers to fuel business success.
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,
“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 and chief technology officer of Rasgo, in a statement.
“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, democratising intelligence, not just the data, and transforming business users into intelligence providers. We’re using AI to change knowledge work forever.”
Jared Parker, co-founder and CEO of Rasgo, added: “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 [large language model] 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.”
