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Quantiphi announces partnership with Databricks to help drive enterprise-wide AI adoption

Quantiphi-announces-partnership-with-Databricks-to-help-drive-enterprise-wide-AI-adoption

Quantiphi, an AI-first digital engineering company, announced its partnership with Databricks, the lakehouse company and pioneer of this new data paradigm. Together, Quantiphi and Databricks will focus on helping enterprise customers to optimize their business workflows with AI which will be enabled by a strong foundation of the Lakehouse platform.

Businesses today are embracing multi-cloud and hybrid cloud environments. As a result, it has become imperative to modernize their data foundation for seamless operations across different environments, and deploy advanced cloud-based technologies – including analytics tools with advanced machine learning (ML) and MLOps capabilities.

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As Databricks Consulting Partners, Quantiphi will accelerate AI-driven innovation for clients across industries. Quantiphi’s in-depth knowledge and deep expertise in helping enterprise customers modernize and democratize their Data and AI footprint at scale are valuable for the partnership with Databricks. Databricks’ Lakehouse Platform is cloud-agnostic and enables users to unify their data warehousing and AI use cases on a consistent platform across multiple infrastructures simultaneously.

“We are delighted to enter into a strategic partnership with Databricks,”. said Asif Hasan, Co-founder, Quantiphi. “By combining the power of Databricks’ Lakehouse Platform and Quantiphi’s advanced AI/ML capabilities, our teams will empower customers to leverage data-driven MLOps and enable enterprise AI success.”

The collaboration is set to actively support customers with various data and AI services such as digital transformation strategy, AI innovation roadmap, MLOps, data modernization and migration, data management, security, and governance implementations. Quantiphi’s team of dedicated applied AI Databricks experts will further help customers implement and scale data engineering, collaborative data science, full-lifecycle machine learning, and business analytics initiatives.