Kazimi secures €2.2M to bring privacy proof security to AI data

Kazimi sits at an important but often overlooked choke point in the AI value chain: the integrity of the behavioral data that trains and drives models. By securing app level event streams and distinguishing real users from bots with privacy preserving proofs, it is trying to ensure that the signals feeding recommendation systems, ad optimisation and fraud models are actually trustworthy. In a world where synthetic traffic and click farms quietly poison datasets, that is strategically relevant. ([media.startupcentrum.com](https://media.startupcentrum.com/en/investment-kazimi-raises-e2-2m/))

For Europe, this is also another example of AI related deep tech that leans into the region’s strengths around privacy and security rather than raw model scale. If Kazimi’s approach works, it gives both advertisers and AI teams a way to clean their inputs without violating GDPR style constraints, which could make European data more competitive as training fuel.

In the broader race to AGI, higher quality, better attributed data will matter as much as parameter counts. Tools that harden the data layer reduce the risk that sophisticated bots and automated traffic quietly bias models in ways that are hard to detect. They also open room for new business models around attestations and verifiable signals, which could become key primitives for agent to agent interactions.