Aug 6, 2026 earnings call — AI-driven growth and product launches
Datadog reported Q2 revenue of $1.12 billion, up 36% year-over-year, and free cash flow of $279 million (25% free cash flow margin).
Revenue $1.1B (est $1.1B) · EPS $0.65 (est $0.58) · Next-quarter revenue outlook $1.1B–$1.1B
Key quotes
"First, AI is a tailwind for Datadog today as cloud consumption grows and drives more use of our platform."
"We held our DASH user conference in June, where we announced over 100 exciting new products and features for our users."
"First, we landed a 6-figure annualized deal with a Fortune 10 company."
Analyst Q&A 13
Largest customer renewal and lower usage
Q (Sanjit Singh · Morgan Stanley): Was the new contract similar duration and why did usage fall — lower unit price from a new commitment or churn/downsell?
A: They would not share many specifics about the customer contract. They renewed the long-time customer, saw a reduction in usage, and chose to fully derisk guidance for the rest of the year while noting the rest of the business is accelerating.
"We renewed the customer. We -- it's a long-time customer using many of our products, but there's not a lot more we can share." — Olivier Pomel (CEO)
Observability needs for inference workloads
Q (Raimo Lenschow · Barclays): As inference grows, how much more observability is needed across GPUs, vector DBs, agents and containers? Is inference a bigger opportunity than renewals?
A: They see opportunity at every layer of the inference stack, from GPUs to agents to tool calls. GPU monitoring and agent monitoring usage have increased, and customers' focus has shifted from validating correctness to optimizing cost.
"We see growing adoption from the products we already have there." — Olivier Pomel (CEO)
CFO conversations and Infinite Cardinality
Q (Gabriela Borges · GS): How are CFO-level discussions changing about Datadog bills and is Infinite Cardinality part of the CFO conversation to control costs?
A: They say customers buy software because it makes or saves money and they must make that case in renewals and upsells. Customers ask for help reining in AI costs, and Infinite Cardinality has been addressed technically and commercially by repackaging metrics, with early but positive feedback.
"And we've solved that from a technical perspective and from a commercial perspective by packaging our metrics a little bit differently." — Olivier Pomel (CEO)
AI lab customers vs hyperscalers
Q (Michael Cikos · Needham): Are the two 7-figure AI lab deals the same as hyperscaler deals, and why are new logos ramping faster now?
A: They are different customers: neuro Labs that didn't exist years ago and hyperscalers. Neuro Labs are using Datadog while training models to observe and optimize training; hyperscalers have similar training workloads but often had homegrown tooling previously. They also noted new logos' contribution to growth has been increasing.
"In this case, these are customers we're getting as they are training models, and they're using us to observe and improve and optimize the training of the models." — Olivier Pomel (CEO)
Terms and stickiness of largest renewal
Q (Aleksandr Zukin · Wolfe Research,): Any changes to duration, discounting, product mix or stickiness in the largest customer's new contract?
A: They declined to comment on specific contract terms. They described their typical enterprise approach as annual-plus commitments with generally volume-based pricing and usage variability, similar to most large customers.
"I won't comment on this other than to say that most of our enterprise customers, as we talked about for a long time, have annual plus and then the pricing is generally volume-based pricing." — David Obstler (CFO)
Q3 guide assumptions and AI model diversity
Q (KeyBanc): Why is Q3 guide a bit below usual sequential guidance and how does diversification of AI models affect Datadog?
A: They applied the same conservative guidance methodology and considered the renewal and the observed usage declines at the largest customer. Model diversification is positive: it increases options and complexity, opens new training markets, and creates opportunities for Datadog to help customers manage complexity and training.
"And so we think the same is going to happen in AI." — Olivier Pomel (CEO)
Bits AI automation and product consumption
Q (Koji Ikeda · BofA): Could Bits AI automation reduce the observability activity that drives Datadog usage?
A: They argue more automation that provides value leads customers to use more Datadog, not less. Bits AI expands beyond alerts to chat, monitoring, detection, coding, tests, and customers using Bits AI deploy more product, dashboards and users — not a zero-sum effect.
"When they use Bits AI, they use more of our product." — Olivier Pomel (CEO)
Sustainability of non-AI acceleration and FedRAMP progress
Q (Samik Chatterjee · JPMorgan): Is non-AI acceleration sustainable and driven by new logos or usage? Any update on FedRAMP High pipeline?
A: The acceleration is broad-based and largely driven by existing customers through volume increases and adoption of newer products; it's sustainable and supported by ongoing R&D and go-to-market investments. On government sales, they are investing, see pipeline traction, and are building certifications like FedRAMP, but deals take time.
"So I mean from what we can tell, it's very broad-based." — Olivier Pomel (CEO)
Bits AI growth and large media deal details
Q (Howard Ma · Guggenheim): How does Bits AI adoption compare to prior expansions and in the $30 million media deal, are multiple products used and why now?
A: Bits AI has widened from alert investigations to chat, monitoring, detection, coding and test generation, and they're changing packaging with AI credits; adoption is broad across those surfaces. For large deals they typically land with two or more products to balance deal speed and later expansion; big consolidation deals are highlighted because they are larger.
"You can have Bits AI manage your monitoring and manage your detection for you." — Olivier Pomel (CEO)
CPU use and infrastructure monitoring demand
Q (Andrew Sherman · TD Cowen): Could CPU demand from agentic AI be an incremental driver for infrastructure monitoring? Any evidence?
A: They see accelerating consumption of infrastructure products across the customer base. A lot of agent work involves coding tools that run on CPUs, so they are seeing substantial related CPU activity.
"we do see an acceleration of consumption of our infrastructure products in general." — Olivier Pomel (CEO)
Excluding largest customer, core growth impact
Q (Brad Reback · Stifel): If you exclude the largest customer's sequential downtick, would core guide be materially higher by several hundred basis points?
A: They declined to speculate on a specific basis-point lift. They reiterated that excluding that customer the business is growing at the same rate and overall the business has been accelerating, giving them confidence in the company's performance.
"the business overall is growing at the same rate. if you exclude that customer, as I said." — Olivier Pomel (CEO)
New customer additions count weakness
Q (Ittai Kidron · Oppenheimer): Why was this quarter weak for new customer additions despite DASH historically boosting additions?
A: Gross customer additions are strong and on trend; variability occurs at the low end border between free and contract, affecting account counts but having little revenue impact. Larger customers above thresholds are trending well.
"Our gross customer additions continue to be strong and on trend line." — David Obstler (CFO)
AI monitoring demand among traditional companies
Q (Andrew DeGasperi · BNP Paribas): Did non-AI-native companies increase demand for AI monitoring tools, especially with open-source model deployments?
A: A year ago volume was small, grew in the second half of last year, and has rapidly accelerated over the past couple of quarters. They see usage from both traditional and AI-native companies, but the category is still early and products and packaging may evolve.
"And now it's been very rapidly accelerating over the past couple of quarters." — Olivier Pomel (CEO)