The company, which is also part of the S&P 500, has established a workforce of over 100 employees in Bengaluru within just two years of entering the Indian market, along with smaller offices in Mumbai and Delhi. It is now investing further to expand its operations.
“We are just two years into our journey in India and are already developing a comprehensive go-to-market strategy — from partnerships to customer success and channels,” stated Namit D’Cruz, Regional Vice President for India and SAARC at Datadog, in an interview with CNBC-TV18.
Globally, Datadog serves over 32,700 clients and employs around 8,100 individuals across more than 60 countries. Initially focused on the U.S. market, the company has since pursued an expansion strategy through Europe and Asia, with India standing out as a vital growth hub.
India strategy
Datadog’s approach in India is based on a hybrid distribution model that capitalizes on partnerships with hyperscalers like Amazon Web Services, Google Cloud Platform, and Microsoft Azure, in conjunction with developing its own partner ecosystem.
The company currently collaborates with approximately 40 partners in India, including QualityKiosk Technologies, Hitachi, and Zeus Global. A key priority is forging services-led partnerships, especially for enterprise clients needing deployment and integration support.
The firm is witnessing strong demand across various sectors, including digital-native businesses, IT services, media, and financial services, while also engaging large enterprises undergoing transformations in cloud and AI.
AI not a threat, but a catalyst
Responding to concerns about AI potentially disrupting SaaS models, Datadog views this transition as an opportunity rather than a threat.
The company has created a specialized large language model for observability, named Toto, which is trained on its telemetry data to support autonomous functions within its platform.
Datadog is also asserting its role as a full-stack provider for AI workloads, facilitating everything from GPUs and LLMs to agents. Approximately 60 of the top 100 global AI firms rely on Datadog for deployment, monitoring, and research.
“AI in production introduces entirely new challenges — including cost management, hallucination risks, model drift, and security. This is where observability becomes essential,” D’Cruz explained.
The company’s long-term objective is to establish autonomous, self-healing systems where AI-driven observability can identify and rectify issues with minimal human oversight.
Datadog is aggressively expanding into security, integrating it seamlessly with its observability stack as companies transition towards DevSecOps.
With high-frequency telemetry data at its foundation, the company perceives security as a natural extension of its platform, providing features that range from code-level security to cloud posture management.
A significant portion of its R&D funding is now being channeled toward AI and security.
Rapid scaling and investment momentum
India has emerged as one of Datadog’s fastest-growing markets globally. The firm has already undergone multiple office expansions in Bengaluru and continues to recruit for various roles in sales, operations, and support.
“We are developing capabilities in India much quicker than in markets like Singapore or Tokyo, mainly due to the rapid demand here,” D’Cruz noted.
The company is expanding its workforce across different functionalities and enhancing its enterprise, mid-market, and commercial teams to foster growth.
Datadog is also addressing the evolving data protection and compliance landscape in India with features like its Sensitive Data Scanner, which enables enterprises to classify, mask, or restrict sensitive data at the source.
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Regulated entities, including financial services firms like Bajaj Finserv and Motilal Oswal Financial Services, are already utilizing the platform.
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As digital transformation accelerates across various sectors, the company anticipates continued broad-based demand, driven by enterprises modernizing their infrastructure and widely adopting AI.
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