Paris-based observability software company Tsuga has raised $35 million in a Series A round as it seeks to build infrastructure designed for an era in which AI systems produce large and increasingly sensitive streams of operational data. The financing was led by Singular, with returning backer General Catalyst joined by new investors DST Global and Quantumlight, alongside Picus and Databricks. The raise follows the company’s $10 million seed round in December 2025 and gives Tsuga further resources to expand a model that keeps customers’ telemetry and AI workloads within their own cloud environments.
Funding and Strategic Backing
Tsuga said its investors bring both continuity and new backing to support an effort to redefine how organisations deploy observability software. Singular and General Catalyst had backed the Paris startup at seed stage, while DST Global, Quantumlight, Picus and Databricks have joined for the Series A, taking total capital raised to $45 million. The participation by Databricks also underscores a commercial partnership focused on enabling clients to direct observability data into its platform for additional analysis.
A Challenge Created by AI Workloads
Conventional observability vendors generally ingest logs, metrics and traces in their own cloud systems, often charging customers according to data volumes or infrastructure growth. Tsuga argues that this approach becomes more expensive and harder to govern as businesses deploy autonomous agents, AI models and more distributed applications, all of which generate continuous telemetry. Its argument is that the next phase of observability requires an architecture built for high data volumes, granular security controls and customer ownership rather than AI features added to existing SaaS products.
A Resident-Data Platform
Tsuga deploys its platform inside a customer’s cloud account instead of requiring telemetry to be moved to a vendor-controlled environment. The company combines managed software with forward-deployed engineers, who work alongside client teams to tune observability environments, reduce noise and limit unnecessary data processing and retention. Its offering also includes automated root-cause analysis on complete, unsampled data, as well as an MCP server and command-line interface that enable developers to build internal agents on their own operational data without moving it outside their security boundary.
Early Commercial Traction
Tsuga was founded in 2024 and launched in December 2025, positioning itself as a provider of “AI-Native Resilient Observability” for enterprises with complex or regulated infrastructure. The company reports that it has already contracted millions of dollars in annual recurring revenue, secured six-figure average contract values and signed customers including Le Monde, Camunda, Buk and Black Forest Labs. These customer examples indicate initial demand from businesses operating multi-cloud environments, supporting sensitive workloads or seeking closer governance of data used to monitor AI systems and infrastructure.
Growth Priorities
The Series A proceeds will be used to add to its team and expand the platform’s deployment capacity, including its forward-deployed engineering workforce. Tsuga also plans to invest in its Skills library, MCP server and agent-building toolchain, which it sees as key components for turning resident telemetry data into practical AI capabilities. The roadmap reflects a broader move in enterprise software toward architectures that treat data residency, operational control and AI readiness as core product requirements rather than optional additions.
Tsuga’s financing gives it a substantial capital base to advance an approach that challenges established observability pricing and deployment models. Its central wager is that organisations will increasingly prefer platforms that keep operational data, analysis and AI agents under their control, particularly as AI-driven systems create more telemetry and stricter governance requirements. The company now needs to turn its early customer traction and investor support into a scalable platform and delivery model as competition increases across the AI-native observability market