Cognita.ai raises $15M to fix enterprise AI’s biggest bottleneck: deployment

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Cognita.ai raises $15M to fix enterprise AI’s biggest bottleneck: deployment

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Cognita.ai, a Chicago-based artificial intelligence company, has raised $15 million in Series A funding to help enterprises move beyond AI pilots to production-grade solutions that deliver measurable business impact. The funding round was led by Nexus […]

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Cognita.ai, a Chicago-based artificial intelligence company, has raised $15 million in Series A funding to help enterprises move beyond AI pilots to production-grade solutions that deliver measurable business impact. The funding round was led by Nexus Venture Partners.

The investment comes at a critical time when enterprises struggle to transform AI experiments into operational solutions. While 87% of enterprises are investing in AI, only 20% successfully deploy solutions into production, according to Cognita.ai.

“Enterprise AI adoption has reached its tipping point,” said Feroze Mohammed, founder and CEO of Cognita.ai, in an exclusive interview with VentureBeat. “The biggest challenges enterprises face isn’t just building AI models — it’s getting them to work in production.”

How Zunō platform cuts AI implementation time from 8 months to 12 weeks

Mohammed, who previously led Hitachi Vantara as COO, identified three major barriers to enterprise AI adoption: data readiness, integration challenges with existing business processes, and lack of AI expertise within organizations.

To address these challenges, Cognita.ai has developed Zunō, a platform that includes accelerators for predictive modeling, intelligent document processing, and advanced graph-based solutions. The company claims its approach reduces typical AI implementation times from 6-8 months to 10-12 weeks.

“Most conventional approaches require long lead times of doing consulting projects, doing a lot of change management with long timelines and long upfront investments,” said Anup Gupta, managing director at Nexus Venture Partners, in an interview with VentureBeat. “Cognita is one of the first times we have come across a business which can talk about demonstrable use cases across various industries.”

The company has already deployed solutions at over 30 enterprises. In one case, Cognita.ai helped a major garage door manufacturer transform its catalog generation process from a six-month cycle to just weeks using generative AI. The solution allows the manufacturer to create virtual door designs and render them in different settings, enabling rapid testing with dealers.

Other successful implementations include a 70% improvement in invoice processing speed and a one percent reduction in customer churn for SaaS clients – metrics that translate to significant revenue impact for large enterprises.

The future of enterprise software: Every stack is being rewritten with AI

The funding will support three primary initiatives: market expansion, intellectual property development, and capability building. Mohammed envisions Cognita.ai becoming “the practical AI company for the enterprise” within five years.

“Every software stack is being rewritten leveraging AI,” said Gupta. “In the next few years, every workflow in all enterprises will have a lot more AI than is being used today.”

This investment reflects a broader trend in enterprise AI, where focus is shifting from experimental projects to practical implementations that deliver clear return on investment. As businesses seek to operationalize AI while maintaining existing systems, Cognita.ai’s approach of building solutions that integrate with current workflows appears particularly timely.

The company plans to expand its AI solution library, advance its Zunō platform, and grow its implementation teams to meet increasing enterprise demand. With offices in Chicago, Silicon Valley, and Hyderabad, Cognita.ai serves clients across manufacturing, healthcare, finance, and technology sectors.

Industry analysts suggest this funding round could signal a new phase in enterprise AI adoption, where practical implementation and measurable outcomes take precedence over experimental pilots. As organizations continue to grapple with AI integration challenges, solutions that can demonstrate concrete business impact while working within existing systems may find increasing traction in the market.

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