Raised Funds of $156 Million for AI-focused Observability Company in Series C Round
Observe, an innovative AI-based observability company, has announced the completion of a $156 million Series C funding round. The round was led by Sutter Hill Ventures, with contributions from Madrona Ventures, Alumni Ventures, Snowflake Ventures, and Capital One Ventures.
This funding will enable Observe to focus on product development, AI innovation, and global hiring. The company's rapid growth is evident in its tripled monthly active user count, doubled enterprise customer base, and a net revenue retention rate of 180%.
Observe's platform is gaining traction among large enterprises and modern SaaS and AI-native firms. Andrew Katz, CTO & Co-Founder at mParticle, uses Observe to cost-effectively handle the scale and complexity of log aggregation needs at Dialpad. Max Wardell, Sr. Engineering Manager at Dialpad, finds Observe's platform invaluable for visibility across their cloud environment, reducing mean time to resolution and operational costs. Oscar Papel, CISO at Truveta, emphasizes the importance of full-stack observability for system resilience, AI, and personalized customer experiences, and invests in Observe's growth.
Core Innovations
Observe's platform features several core innovations that set it apart in the observability landscape.
AI Agents for Observability
Observe incorporates AI agents within its observability product to help engineers quickly identify and fix software issues amid increasingly complex AI-driven environments. These agents go beyond simple anomaly detection by assisting with instrumentation and complex diagnostics, effectively transforming the troubleshooting workflow.
O11y Data Lake™
This is a specialized, scalable, and cost-efficient data lake optimized for observability data such as logs, metrics, traces, and events streamed in real time. It supports open standards like OpenTelemetry and Apache Iceberg, enabling enterprises to centralize telemetry data in their data lakes for better scalability and cost control.
O11y Knowledge Graph™
Observe builds a real-time contextual model of the entire system, mapping resources, services, deployments, and incidents. This contextual understanding addresses the "context bottleneck" by connecting disparate data points, which is critical in modern, distributed environments.
Model Context Protocol (MCP) Server
Observe introduced this protocol server to enable developers to seamlessly access observability data from AI coding tools and large language models (LLMs), helping developers work within their existing workflows and further integrating AI capabilities in software development processes.
Addressing AI Complexity
Observe acknowledges that the proliferation of AI agents interacting dynamically in networks brings new challenges. Their solutions aim to manage the operational complexity of hundreds or thousands of AI agents, helping organizations quickly pinpoint root causes when issues arise.
These innovations reflect a broader industry shift where enterprises are moving telemetry and observability data into scalable data lakes, emphasizing the integration of AI not just for detection but for intelligent remediation, and building rich contextual models to make observability data actionable.
Dennis Bragfeldt, Chief Architect at Topgolf, finds Observe's data lake-based architecture cost-effective and scalable for unifying data from hundreds of sources. Sean Leach, Partner at Capital One Ventures, believes Observe is uniquely positioned to help enterprises build more reliable agents and applications while containing costs at scale.
With this new funding, Observe is poised to continue its growth and innovation in the AI-powered observability space, addressing the complex needs of modern software development and AI-driven environments.
Investing in Observe's Series C funding round allows for advancements in finance, as the raised funds will be utilized for product development, AI innovation, and global hiring within the technology sector. The unique technology offerings of Observe, such as AI agents for observability, O11y Data Lake, O11y Knowledge Graph, Model Context Protocol (MCP) Server, and their data lake-based architecture, are disrupting the observability landscape by integrating AI not just for detection but for intelligent remediation, and building rich contextual models to make observability data actionable.
