The person who helped build Datadog into a $40 billion observability company is betting his next venture on a contrarian idea: enterprise IT service management is broken, and bolting chatbots onto ServiceNow won’t fix it.
Amit Agarwal, former Datadog president and chief product officer, launched Standard Template Labs this week with $49 million in seed funding. The round was co-led by Iconiq and CRV, valuing the company at $300 million before it has shipped a product to paying customers.
The Thesis
Most enterprise AI deployments in IT service management follow the same pattern: add a conversational layer on top of existing ticketing systems, then hope the AI can route requests faster than humans. Agarwal argues this approach fails because the underlying architecture wasn’t built for automation.
Standard Template Labs (STLabs) is building an AI-native platform designed to resolve IT requests, not just categorize them. The difference matters. Current tools track that your laptop needs reimaging and route the ticket to the right team. STLabs wants to actually execute the reimage without human intervention.
The platform maintains what the company calls a “digital twin” of the enterprise - a constantly updated model mapping people, systems, services, and policies. When a request comes in, the AI has enough context to understand both what needs to happen and what’s allowed to happen, then orchestrates the actual resolution.
The Business Bet
IT service management is a $6 billion market that enterprises love to complain about. ServiceNow dominates, and its stock price reflects enterprise unwillingness to switch. But there’s a gap: ServiceNow excels at tracking and routing, not autonomous execution.
The bet is that generative AI changes what’s possible. Language models can now interpret ambiguous requests (“my VPN isn’t working on my new laptop when I’m at the Chicago office”) well enough to diagnose root causes. Agent frameworks can execute multi-step workflows. The missing piece was building an IT-specific system that combines both with enterprise policy enforcement.
STLabs also ships a module called Axiom as an alternative to traditional configuration management databases (CMDBs). It uses AI to inventory IT assets and flag security compliance issues, essentially automating the data collection that makes everything else possible.
The Pedigree Play
Agarwal spent 13 years at Datadog, joining early and serving as president and CPO through its IPO and subsequent growth to a $40 billion market cap. That track record is worth something to investors: Iconiq called this its first-ever startup incubation, meaning the firm worked with Agarwal on company formation rather than just writing a check.
The Iconiq relationship goes back a decade. Partner Matt Jacobson led the firm’s early Datadog investment in 2015 and maintained the connection as Agarwal rose through leadership.
Who Wins, Who Loses
Winners:
- IT teams drowning in tickets. If STLabs works as described, requests that take days of coordination could resolve in minutes. The humans still employed focus on judgment calls, not password resets.
- The enterprise AI middleware category. A credible Datadog alumni entrant validates that enterprise operations is a legitimate AI application category, not just a demo layer.
Losers:
- ServiceNow’s expansion narrative. ServiceNow has its own AI story, but STLabs is positioning directly against the idea that AI-enhanced ticketing is enough. If enterprises start demanding resolution over routing, ServiceNow’s platform approach looks less comprehensive.
- IT support staff. The pitch is explicitly about automating work currently done by humans. Agarwal’s framing emphasizes freeing people from “manual triage” but the headcount math is straightforward.
A $300 million pre-revenue valuation for an IT automation startup would have seemed rich two years ago. In the current market, where enterprise AI deals are competitive and Datadog pedigree carries weight, it reflects what investors will pay for a credible shot at the problem.