French observability startup Tsuga lands €30 million to expand AI agent platform

Jun 23, 2026 - 13:00

Tsuga, a Paris-based innovator in AI-Native Resilient Observability, today announced it has raised €30 million ($35 million) in a Series A funding round to scale its GTM motion and accelerate the rollout of their AI agent platform.

The round is led by existing investor Singular, with participation from General Catalyst alongside new investors DST Global Partners and Quantumlight. Picus and Databricks Ventures are among the additional investors participating in the round.

“The incumbents built good businesses on a model that no longer works. Sending your telemetry to a vendor’s cloud made sense when data volumes were manageable and AI was not writing and deploying your code. Neither of those things is true any more. Every customer we speak to is paying more for observability than they were two years ago and getting less reliable coverage. We built Tsuga to end that,” says Gabriel-James Safar, co-founder and CEO, Tsuga.

Tsuga’s Series A sits within a 2026 funding pattern in which capital has continued to move into infrastructure layers that support AI deployment, software delivery, cloud operations, enterprise data control and agent governance.

The closest French comparisons are OpsMill and Kestra, both Paris-based, which raised €11.9 million and €21 million respectively for infrastructure data management and workflow orchestration.

Across the wider European market, larger rounds such as Verda’s €100 million AI cloud infrastructure financing, Cloudsmith’s €61.5 million Series C for AI-driven software supply chains and Conduct’s €51 million Series A for enterprise systems readiness indicate investor attention to the operational foundations required for AI adoption.

Against that backdrop, Tsuga’s observability-focused round adds a French AI infrastructure example specifically centred on telemetry control, cloud deployment architecture and enterprise monitoring costs.

“By staying out of the data path entirely, Tsuga removes every structural disadvantage the rest of the market is built on. The infrastructure tax disappears. The sampling compromise disappears. The AI governance gap disappears. What is left is a better platform at a lower cost, inside the customer’s own environment,” adds Henri Tilloy, Partner at Singular.

Founded in 2024, the platform deploys inside the customer’s own cloud across any environment so telemetry never leaves their control, infrastructure costs are reportedly eliminated at source, and AI runs on complete, unsampled data.

Six months after exiting stealth, Tsuga has grown to several millions in revenue with average contract values in six figures, and customers including frontier model labs like Black Forest and enterprise customers like Le Monde, Camunda, and Buk.

According to the company, the observability industry has run the same playbook for decades: ingest customer telemetry, store it in a third party cloud, and charge exponentially more as volumes grow.

The AI era has made that approach untenable: every agent loop, every autonomous deployment, every token interaction generates observability data at volumes legacy platforms were never built to handle. Ingestion costs compound. Sampling increases as customers manage their spiraling spend. Governance gaps open as sensitive AI interaction data flows to third-party clouds.

Tsuga says platforms that dominated the last era are not struggling because of a feature gap. They are struggling because their entire architecture was built on an assumption the AI era has made obsolete.

The platform deploys inside the customer’s own cloud account, across Microsoft Azure, AWS, Google Cloud, and regional sovereign clouds, so telemetry never leaves their environment. There is no infrastructure tax, no duplication cost, and no sampling.

Pricing is a single rate per GB of consumption, and costs allegedly fall as Tsuga’s engineers tune the environment over time.

“Tsuga has the architectural scalability, flexibility and distributed platform support that the coming generation of AI-native applications and agents require in their observability platform. This is a step-function change only possible because of their innovation across the full stack, from the storage layer to the business model,” says Alexandre Momeni, Partner of General Catalyst.

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