Why enterprises are betting on Observe Inc. to solve cloud-scale troubleshooting with AI

Observe Inc., the San Mateo-based AI observability platform developer, has raised $156 million in a Series C round led by Sutter Hill Ventures, with participation from Madrona Ventures, Alumni Ventures, Snowflake Ventures, and Capital One Ventures. The funding, announced on July 30, 2025, positions Observe Inc. as one of the fastest-scaling infrastructure software firms in the AI-enabled telemetry and developer tooling space.

This new capital comes on the back of robust financial performance. Over the past year, Observe Inc. has tripled its revenue, doubled its enterprise customer base, and achieved a net revenue retention of 180 percent. Monthly active users also tripled, while the platform ingested more than 150 petabytes of telemetry data across logs, metrics, traces, and events. The platform’s core architecture—centered around an open observability data lake—has helped it attract enterprise workloads that previously relied on legacy vendors like Splunk, Datadog, and Elasticsearch.

Why are enterprises moving to Observe Inc.’s platform instead of traditional observability tools?

According to internal benchmarks shared by Observe Inc., the company’s offering is more than just a low-cost alternative to legacy monitoring stacks—it represents a shift to a data-lake-based observability paradigm that supports scale, context, and agentic AI workflows.

At the foundation is the O11y Data Lake, a telemetry-optimized architecture that streams and stores observability data in real time using open standards such as OpenTelemetry and Apache Iceberg. On top of this, the O11y Knowledge Graph™ maps entities such as services, users, deployments, and incidents into a real-time contextual model of the user’s entire system. This allows teams to correlate anomalies, root causes, and performance bottlenecks across layers of infrastructure, apps, and services with minimal manual tuning.

What makes Observe Inc. particularly distinct is its O11y AI SRE component—a layer of agentic AI that not only detects issues but also assists in instrumenting systems, accelerating root-cause analysis, and closing incident response loops. Analysts note that these end-to-end capabilities allow developers to troubleshoot cloud-scale applications up to 30 percent faster compared to traditional observability suites.

How are enterprise users validating Observe Inc.’s value proposition in real-world use cases?

Institutional customers adopting Observe Inc. cite reduced mean time to resolution (MTTR), lower observability costs, and improved developer efficiency as key drivers for switching. At Tekion, for example, Chief Technology Officer Binu Mathew explained that the company struggled with scaling commercial and open-source tools, leading to unacceptable engineering overheads. By moving to Observe Inc., the team gained a unified platform that provided visibility across logs, metrics, and traces without the need for constant manual reconfiguration.

Topgolf and Toptracer echoed similar sentiments. Dennis Bragfeldt, Chief Architect, highlighted the cost efficiency of Observe Inc.’s ingestion model and the architectural clarity delivered by the knowledge graph.

At Dialpad, a unified view of all aspects of call performance—spanning infrastructure to user experience—enabled the company’s engineering teams to accelerate issue detection and remediation by up to 30 percent. Truveta’s security and infrastructure teams also credited Observe Inc. with reducing operational costs while enhancing visibility across their cloud environments.

What recent innovations have strengthened Observe Inc.’s position in the observability market?

Earlier in 2025, Observe Inc. launched its Frontend Observability suite, designed to bring real user monitoring (RUM), mobile observability, and synthetic monitoring under one umbrella. The rollout included browser RUM capabilities using OpenTelemetry SDKs and performance dashboards that highlight core web vitals, HTTP errors, and page latency. Mobile RUM was launched in private preview, enabling observability across iOS and Android environments via SDKs and integrations with Embrace’s telemetry platform.

The full-stack observability suite allows engineering and DevOps teams to trace performance issues from front-end applications back through APIs and into backend infrastructure. Observability begins at the first customer interaction, according to Chief Executive Officer Jeremy Burton, and extends all the way into the service logic.

By incorporating synthetic monitoring and open-standards data collection, Observe Inc. aims to eliminate vendor lock-in and foster community-driven visibility tooling.

Why do institutional investors see long-term value in Observe Inc.’s AI-native observability model?

Backers such as Capital One Ventures and Snowflake Ventures emphasized that the company’s architecture aligns with macro trends in AI deployment and telemetry scale. Sean Leach of Capital One Ventures described observability as foundational to personalized experiences and AI operations at scale. Snowflake Ventures’ Director Harsha Kapre noted that AI is only as good as the data it acts upon—and that Observe Inc. is uniquely positioned to power cost-efficient and context-rich data lakes for AI applications.

Analysts across institutional platforms cite three core trends converging in Observe Inc.’s favor: (1) the migration from siloed tools to unified observability platforms, (2) the scaling of AI workloads that demand contextual telemetry insights, and (3) the rise of OpenTelemetry as the de facto standard for observability interoperability. Many enterprise IT teams are now rebuilding their incident response and monitoring stacks from the ground up, with Observe Inc. emerging as a top contender.

What does Observe Inc. plan to do next with its $156 million Series C raise?

Observe Inc. has earmarked the Series C funds for three core initiatives: expanding its AI development team, advancing its knowledge graph and agentic AI architecture, and scaling go-to-market operations internationally. The company also plans to double down on OpenTelemetry community involvement and ecosystem integrations.

Given the rise of AI agents in production environments, Observe Inc. is increasingly seen as not just a monitoring platform, but as a real-time decision support layer for software infrastructure. As software-defined systems grow more autonomous, analysts expect AI-native observability to become indispensable—not optional.

Can Observe Inc. become the Datadog of the AI-native observability era?

Observe Inc.’s current trajectory suggests it is more than a niche disruptor—it is a category reshaper. By replacing piecemeal observability stacks with an AI-native, open-lake-based approach, it is offering enterprise IT teams not only cost advantages but a new operational model for debugging and performance optimization.

While traditional players like Splunk and Datadog continue to dominate in established segments, they are often constrained by licensing complexity and architectural rigidity. Observe Inc., by contrast, appears to have built for the scale, modularity, and AI augmentation that modern systems demand.

For now, investor confidence is high and customer retention figures are among the best in class. If Observe Inc. executes on its roadmap and maintains platform flexibility, it may soon become the default observability layer across next-generation cloud-native environments.