Noogata Secures $12M Seed Funding Round for its No-Code Enterprise AI Platform
The combination of AI and no-code software development platforms are accelerating efforts to scale enterprise applications, including data collection, modeling and analysis.
Those are among the goals of Noogata, a no-code AI startup targeting enterprise data analytics tools that can be built by non-programmers.
The two-year-old startup based in Tel Aviv, Israel, announced a $12 million seed funding round this week led by Team8 Capital with participation from Skylake Capital.
Low-code for AI is touted as allowing novice developers and data scientists alike to use AI building blocks to quickly spin up enterprise applications. Noogata’s framework initially focuses on data analytics tools that could be used across a company’s operations. Other use cases are in the pipeline, the startup said Tuesday (March 16).
“A user would use our platform to select a use case and deploy the different blocks within,” Assaf Egozi, Noogata’s co-founder and CEO, told EnterpriseAI.com. “Then [they would] connect it to their enterprise data—typically from their data warehouse—and automate it end-to-end on our platform. The customer doesn't need to design or code the models and other parts of the analytics pipeline.”
The startup notes its no-code AI platform can be integrated with existing enterprise data systems, eliminating the need for internal development while expanding capabilities beyond narrow, off-the-shelf tools.
Those AI-based capabilities also would allow novice users to expand beyond traditional business intelligence tools to forge new “self-service” analytics tools, Egozi said.
Along with scaling enterprise data analytics, the startup is also looking to extend is no-code AI framework to other applications. “We are also working on use cases to drive automation and personalization using prediction,” Egozi added. Examples include demand forecasting to optimize manufacturing.
The team also includes business consulting veterans from KPMG and McKinsey & Company. “Our startup team is fairly unique as it has equal parts of engineer [and] data-scientist,” Egozi said.