Acceldata Launches Hybrid-Native Platform for Enterprise AI

Acceldata has launched an autonomous data and AI platform to help enterprises run AI workloads across distributed data environments, as companies face growing challenges in governance, infrastructure readiness, and fragmented systems. 

The platform is now available globally and targets enterprises operating across cloud, on-premises, hybrid, and sovereign infrastructure. The launch comes as enterprises expand AI adoption but struggle to scale systems built on fragmented data architectures. 

Acceldata said the platform introduces a new compute model that allows analytics and AI agents to operate on enterprise data wherever it resides. Built on the company’s xLake architecture, the platform routes workloads across infrastructure, enforces governance, and manages data quality in hybrid-native environments.

“The lakehouse architecture was built for human access. It broke in the agentic era,” Rohit Choudhary, Co-founder and CEO of Acceldata, said in a statement.

The company said enterprises increasingly face operational complexity as they manage data across multiple cloud and on-premises systems. Many organisations also face rising infrastructure costs and inconsistent data quality as they scale AI initiatives, and traditional systems built around centralised data movement are becoming harder to maintain.

“We started Acceldata with the conviction that enterprise data would never consolidate, and that hybrid would be the durable reality,” Choudhary said. He added that enterprises, including those in India’s growing global capability centre (GCC) ecosystem, are increasingly operating across cloud, on-premises, and sovereign environments with governance requirements.

India’s emerging GCC hub, particularly in cities such as Bengaluru, Hyderabad, Pune, and Chennai, is where enterprises increasingly drive AI, cloud, and data transformation initiatives. Acceldata said its engineering teams in Bengaluru work with global customers and GCCs to address distributed enterprise data challenges.

The platform also includes features such as workload routing for analytics and AI, governance enforcement, infrastructure optimisation, and observability tools to monitor data pipelines and detect anomalies. Acceldata said these capabilities aim to help enterprises improve trust in AI systems and reduce operational costs.

“We’re building the operating system for the AI-native enterprise, one runtime that spans every cloud, data centre, and edge, so intelligence is no longer trapped by where the data happens to live,” said Ashwin Rajeeva, Co-founder and CTO at Acceldata.