Observe Raises $156M to Redefine AI-Era Observability with Data Lake & AI SRE

The rapid acceleration of artificial intelligence has inadvertently sparked a significant challenge for IT departments: an overwhelming flood of telemetry data. Every new AI service and model generates a torrent of logs, traces, and metrics, transforming observability – the practice of understanding a system’s internal state from its external outputs – from a background function into one of the most substantial line items in modern enterprise IT budgets.

Into this burgeoning challenge steps Observe, a San Mateo-based startup that recently secured $156 million in Series C funding. The company aims to redefine observability for the AI era, promising engineering teams faster answers and significantly reduced costs. Observe positions itself against established market giants such as Splunk, Datadog, and Elasticsearch, offering a platform built around a telemetry data lake, a real-time knowledge graph, and AI-powered Site Reliability Engineering (SRE).

A primary hurdle for data teams today is the fragmented nature of collected information. Telemetry often disperses across various tools, forcing engineers to manually piece together a comprehensive view during critical outages or performance bottlenecks. Compounding this, traditional observability platforms frequently employ pricing models based on data ingestion or storage, leading to spiraling costs as AI workloads expand. For many organizations, what began as an operational safeguard has morphed into a considerable budget headache—a gap Observe intends to bridge.

Binu Mathew, CTO at Tekion, echoed this sentiment, noting that their existing observability tools struggled to scale with their explosive growth. “We had tried major commercial and open-source tools, but both resulted in escalating costs and constant tuning efforts that drained engineering resources,” Mathew stated. “Observe gave us a cost-effective unified platform for logs, metrics, and traces, with the ability to correlate across all of them.”

Observe’s platform is designed to consolidate all logs, metrics, and traces into a single Telemetry Data Lake. Data is ingested in real time and stored in an open, compressed format, which the company claims ensures predictable storage costs even as workloads scale. This architecture also purportedly eliminates the need for the heavy indexing and continuous tuning common in older systems.

Layered atop the data lake is Observe’s live Knowledge Graph, which intelligently maps the connections between services, infrastructure components, deployments, and incidents. This contextual understanding, the company asserts, allows data teams to bypass the manual correlation often required during system failures. The final component is the AI SRE, described as an always-on system capable of detecting anomalies, pinpointing root causes, and recommending or even triggering automated fixes. Collectively, these elements are designed to accelerate troubleshooting and alleviate the operational burden of managing observability at scale.

Andrew Katz, CTO and Co-Founder at mParticle, emphasized the platform’s scalability and cost-effectiveness. “Our customers rely on us to unify data from hundreds of sources, which demands a highly scalable and efficient infrastructure,” Katz explained. “Observe’s data lake-based architecture allows us to scale observability much more easily and cost-effectively than traditional solutions.”

While the observability market is dominated by mature platforms, many of these rely on architectures that struggle to manage the sheer volume and complexity of data generated by today’s AI workloads. The constant demands for indexing, tuning, and storage oversight in legacy systems have created an opportunity for platforms that can simplify operations while keeping costs in check. Observe aims to capitalize on this by promoting a model designed to handle modern data demands without the same maintenance overhead.

Large-scale deployments demonstrate the platform’s practical application. Observe stores telemetry in Apache Iceberg format, granting customers full control over their data and preventing vendor lock-in. The system also leverages OpenTelemetry for data collection, facilitating seamless integration with existing pipelines and tooling. The company recently enhanced its capabilities by adding an MCP server, enabling external AI SREs to directly interact with its observability context, thus opening avenues for partners and other tools to participate in automated incident workflows powered by the same real-time knowledge graph.

Observe cites compelling customer success stories, including a major international bank that reportedly replaced Splunk with Observe, initially processing 30 TiB of compliance logs daily and later scaling to nearly 100 TiB with over 3,000 users. The bank has since retired Splunk entirely and plans to transition from AppDynamics to an OpenTelemetry-native Application Performance Monitoring (APM) strategy.

The company’s growth metrics underscore its rising traction: over the past year, Observe has tripled its revenue, doubled its enterprise customer base, and now handles more than 150 petabytes of data. It also boasts an impressive net revenue retention rate of 180%, indicating that existing customers are expanding their usage over time. Noteworthy clients include Topgolf, which uses Observe to align ingestion costs directly with resource usage, and Dialpad, which reports a 30% reduction in troubleshooting time.

Investors are taking notice. Capital One Ventures, for instance, sees Observe as central to system reliability. Sean Leach, a partner at the firm, described full-stack observability as “foundational for AI” and crucial for tracking resource utilization and delivering tailored customer experiences. He affirmed Capital One’s backing of Observe due to its “bold vision for modern observability.” Snowflake Ventures has also deepened its commitment, recognizing that Observe’s telemetry-first design naturally complements the Snowflake Data Cloud, paving the way for joint solutions in enterprise environments.

With this substantial $156 million Series C infusion, Observe gains significant runway to further develop its platform, introduce new features, and intensify its competitive push in a market ripe for disruption.