Tsuga Raises $35 Million Series A

Tsuga, the enterprise observability platform that runs in your cloud, led by Gabriel-James Safar, Sébastien Deprez, and the team, has announced its Series A, led by Singular, with General Catalyst also participating, both of whom backed its $10 million seed round in December 2025. They are joined by new investors DST Global and Quantumlight, with Picus and Databricks also participating. 

The Problem.

Observability has followed the same model for decades: telemetry is ingested, stored in vendor-controlled clouds, and priced based on growing infrastructure usage. The rise of AI is exposing the limitations of that approach. Every agent loop, autonomous workflow, and model interaction generates data at a scale that legacy observability platforms were never designed to handle. As data volumes increase, ingestion costs escalate while governance and security challenges grow, particularly when sensitive AI-generated data is routed through third-party systems.

The challenge is not a lack of features. The architectures that defined the previous generation of observability were built around assumptions that no longer hold in an AI-native world. AI-Native Resilient Observability was created to address that fundamental shift.

While many vendors are responding by layering AI capabilities onto legacy platforms, the underlying architectures remain optimized for human-centric workflows rather than autonomous systems and AI-driven operations.

What We Built.

Tsuga was built around a simple principle: observability platforms should create value, not add cost and complexity. Traditional SaaS models often tie pricing to growth, turning increasing data volumes into rising infrastructure expenses while moving critical telemetry outside the customer’s environment.

Tsuga takes a different approach by deploying directly within the customer’s cloud. Data remains under the customer’s control, eliminating infrastructure markups and reducing governance concerns. A team of forward-deployed engineers works alongside customers to optimize observability environments, reduce noise, and lower the volume of data that must be processed and retained.

Because telemetry stays within the customer’s environment, AI-powered capabilities do as well. Automated root cause analysis operates on complete, unsampled data, while the Tsuga MCP server and CLI enable engineering teams to build and deploy their own agents within existing security boundaries. The result is an observability platform designed to deliver operational intelligence, control, and efficiency without compromising data ownership.

Why These Investors.

The participation of existing investors Singular and General Catalyst in the Series A reflects continued conviction from partners who have closely followed the company’s progress, product development, customer adoption, and execution over time.

The addition of DST Global, QuantumLight, Picus, and Databricks highlights growing confidence in the long-term shift toward sovereign, AI-native infrastructure and the emergence of a new observability category built around data ownership, security, and operational intelligence.

The strategic investment from Databricks further strengthens this vision. Through the partnership, customers can integrate Tsuga observability data directly into Databricks environments, creating a more unified foundation for analytics and AI. Together, the companies share a belief that data, observability, and intelligence should operate within the customer's own environment rather than relying on third-party infrastructure.

Six Months In.

Since launching in December 2025, Tsuga has achieved significant early commercial traction, securing millions of dollars in contracted ARR and six-figure average contract values.

Customers including Le Monde, Camunda, Buk, and Black Forest Labs are using the platform across mission-critical environments. Deployments span election-related infrastructure monitoring, multi-cloud environments with stringent data residency requirements, and observability for cutting-edge AI workloads, demonstrating demand for AI-native observability across a range of complex use cases.

What Comes Next.

The new funding will support team expansion and accelerate platform development across key areas, including forward-deployed engineering, the Skills library, the MCP server, and the agent-building infrastructure that enables customers to turn observability data into actionable AI capabilities.

The focus remains on building a category-defining platform for AI-Native Resilient Observability while helping organizations gain greater visibility, control, and confidence in the infrastructure that powers their operations.