The firm, which is also part of the S&P 500, has built a team of over 100 employees in Bengaluru within just two years of entering India, alongside smaller offices in Mumbai and Delhi. The company is now investing further to scale operations.
“We are just two years in India and are already building out the full go-to-market stack — from partnerships to customer success and channels,” Namit D’Cruz, Regional Vice President for India and SAARC at Datadog, told CNBC-TV18.
Globally, Datadog has over 32,700 customers and around 8,100 employees, with operations across more than 60 countries. While the company was initially US-focused, its expansion strategy has since moved through Europe and Asia, with India emerging as a key growth market.
India strategy
Datadog’s India playbook hinges on a hybrid distribution model — leveraging hyperscaler partnerships with Amazon Web Services, Google Cloud Platform and Microsoft Azure, while simultaneously building its own partner ecosystem.
The company currently works with around 40 partners in India, including QualityKiosk Technologies, Hitachi and Zeus Global. A major focus is on services-led partnerships, particularly for enterprise customers that require deployment and integration support.
“We are investing more on the services side in India because many customers prefer partners to handle implementation,” D’Cruz said.
The company is seeing traction across sectors such as digital-native firms, IT services, media and financial services, while also engaging with large enterprises undergoing cloud and AI transformation.
AI not a threat, but a catalyst
Addressing concerns around AI disrupting SaaS models, Datadog sees the shift as an opportunity rather than a risk.
The company has developed a purpose-built large language model for observability, called Toto, which is trained on its telemetry data and powers autonomous capabilities within its platform.
Datadog is also positioning itself as a full-stack provider for AI workloads, supporting everything from GPUs and LLMs to agents. Around 60 of the top 100 AI companies globally use Datadog for deployment, monitoring and research.
“AI in production brings entirely new challenges — from cost management and hallucination risks to model drift and security. That’s where observability becomes critical,” D’Cruz said.
The company’s long-term vision is to build autonomous, self-healing systems, where AI-driven observability can detect and resolve issues with minimal human intervention.
Datadog is also expanding aggressively into security, integrating it tightly with its observability stack as enterprises move towards DevSecOps.
With high-frequency telemetry data at its core, the company sees security as a natural extension of its platform, offering capabilities ranging from code-level security to cloud posture management.
A significant portion of its R&D investments is now directed towards AI and security.
Rapid scaling and investment momentum
India has become one of Datadog’s fastest-scaling markets globally. The company has already moved through multiple office expansions in Bengaluru and continues to add roles across sales, operations and support functions.
“We are building capabilities in India much faster than in other markets like Singapore or Tokyo, largely because of the pace of demand here,” D’Cruz said.
The company is hiring across functions and strengthening its enterprise, mid-market and commercial teams to drive growth.
Datadog is also addressing India’s evolving data protection and compliance landscape through features like its Sensitive Data Scanner, which allows enterprises to classify, mask or restrict sensitive data at source.
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The platform is already being used by regulated entities, including insurance and financial services firms such as Bajaj Finserv and Motilal Oswal Financial Services.
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As digital transformation accelerates across sectors, the company expects demand to remain broad-based, driven by enterprises modernizing their infrastructure and adopting AI at scale.
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