Key takeaways
- HPE appoints Bhawna Agarwal as MD of India business, succeeding Som Satsangi.
- Agarwal, with 25 years of experience, previously led HPE's compute business unit.
- Celebrate HPE's 6001st 'Made in India' server, enhancing local manufacturing initiatives.
- Launch HPE Private Cloud AI solution to accelerate AI deployment for enterprises.
- Integrate NVIDIA's technology with HPE's capabilities for streamlined AI workload management.
Hewlett Packard Enterprise (HPE), has appointed Bhawna Agarwal as senior vice president and managing director of HPE India, effective immediately. She takes over the leadership of HPE’s India business from Som Satsangi, who is retiring after more than 27 years of service with the company.
Agarwal joined HPE in 2019 and has since led the compute business unit and growth team. In the past year, she has also been overseeing Account Management and Industry Verticals for India. With over 25 years of leadership experience across digital start-ups, media houses, and large consumer tech companies, Agarwal brings a wealth of expertise to her new role.
Agarwal expressed her enthusiasm about her new role: “I look forward to building on the strong foundation laid by Som and continuing to drive growth, scaling our impact and innovation in the region.”
Recently, Agarwal and Satsangi celebrated the inauguration of HPE’s 6001st ‘Made in India’ server with the union minister Ashwini Vaishnaw, as part of HPE’s “Make in India” initiative.
HPE also launched its HPE Private Cloud AI solution in India, aiming to help enterprises deploy generative and agentic AI applications swiftly and at scale. The integrated, self-service AI cloud platform enables rapid development and deployment of AI workloads, significantly reducing the time from experimentation to real-world implementation.
HPE Private Cloud AI integrates NVIDIA’s AI computing, networking, and software stack with HPE’s AI storage, compute capabilities, and the HPE GreenLake cloud.
The platform simplifies AI deployment, monitoring, and optimisation, offering enterprises a unified interface with full lifecycle management and deep observability insights across hybrid environments. It includes resource management and AIOps features and is available in flexible configurations to support many AI use cases.
