Artificial intelligence continues to attract major bets from technology leaders, with Databricks confirming its investment in a new venture launched by Naveen Rao, former head of AI at Intel. The move signals growing interest in AI-focused hardware innovation as companies seek to overcome computing bottlenecks that limit large-scale model performance.
Rao, a recognized figure in the AI industry, is setting up a startup aimed at building specialized infrastructure for artificial intelligence workloads. His background includes founding Nervana Systems, later acquired by Intel, where he went on to lead the company’s AI efforts. Now, with a sharpened focus on hardware designed for the next generation of AI applications, Rao’s venture has quickly gained the attention of investors.
Databricks, which has become a leading platform in data and AI, sees the partnership as strategic. The company has been building tools that help enterprises unify their data pipelines with AI workflows, and improved hardware efficiency is a natural extension of its vision. By supporting Rao’s startup, Databricks is aligning itself with efforts to accelerate model training and inference at scale.
The global AI ecosystem is currently constrained by high computing costs and energy-intensive infrastructure. Even as cloud providers and chipmakers race to supply GPUs and TPUs, the demand for purpose-built hardware that can handle massive data volumes more efficiently has surged. Rao’s new company is expected to design hardware optimized for large-scale model deployment, potentially lowering costs and improving accessibility for enterprises worldwide.
Industry analysts believe this move represents a broader shift in AI investment priorities. While software platforms and model innovations have captured much of the spotlight, hardware is increasingly recognized as the foundation for sustainable AI adoption. A new wave of startups is emerging in this domain, tackling challenges from energy efficiency to throughput performance.
For Databricks, the bet reflects a deeper commitment to shaping the AI stack from infrastructure to application. The company has been expanding its footprint with products like Databricks Lakehouse AI, aiming to simplify model development and deployment for businesses. By backing a hardware-focused venture, it is also ensuring that the ecosystem it relies on keeps pace with enterprise AI adoption.
Rao’s track record lends credibility to the effort. Nervana Systems was one of the earliest companies to pioneer AI-specific chips before its acquisition by Intel in 2016. At Intel, Rao helped steer AI research and development, providing him with insights into the scaling challenges facing enterprises. His new company, while still in early stages, is expected to combine hardware design with software co-optimization, addressing both efficiency and usability.
The timing of the announcement is significant. With generative AI workloads growing exponentially, enterprises are facing rising infrastructure costs and supply chain bottlenecks. Traditional GPU-based systems are often expensive and difficult to scale, leaving room for innovation in custom architectures. Rao’s venture appears positioned to target these gaps, aiming for solutions that balance performance with sustainability.
Experts point out that AI hardware investments often require long development cycles and substantial capital. However, the strategic involvement of companies like Databricks provides early validation and may help attract further funding. This collaboration also signals that software and data platform players are willing to partner in hardware innovation to ensure long-term ecosystem growth.
For enterprises in India and globally, the potential impact could be far-reaching. More efficient AI infrastructure would lower the barrier to entry for companies experimenting with advanced models, while reducing costs for those already deploying large-scale systems. In markets where cost efficiency and scalability are paramount, such innovations could accelerate adoption across industries from finance to healthcare.
The announcement adds to the growing list of AI-related ventures receiving high-profile backing in 2025. As competition intensifies among cloud providers, chipmakers, and AI platforms, the interplay between software and hardware will shape the trajectory of the sector. With figures like Rao leading new initiatives, the ecosystem appears set for a new chapter of hardware-software integration.
While details on the scale of Databricks’ investment and the startup’s roadmap remain limited, the partnership underscores how critical infrastructure innovation has become for AI’s future. For Databricks, it positions the company not just as a data and AI software provider but as a stakeholder in the foundational technologies powering the industry.
The coming years will test whether Rao’s venture can deliver breakthroughs that address the compute-hungry nature of AI models. If successful, it could play a key role in shaping how enterprises and developers alike access and scale artificial intelligence. For now, Databricks’ support highlights both the urgency and the opportunity in building the next generation of AI hardware.