Skip to content

Cosmian

Paris company building privacy-by-default encryption, searchable encryption and confidential-computing tooling for protecting data in use.

Visit Website ↗ + Add to Compare Claim This Company
53/100Incremental Innovator

Overview

Cosmian, founded in Paris in 2018 by Sandrine Murcia and Bruno Grieder, develops cryptography-based tools for computing on protected data, including searchable and functional encryption and confidential-computing deployments with Intel technology.

In June 2022 it raised €4.2 million led by La Banque Postale’s 115K fund and Elaia Partners, and launched a secure computation platform aimed at making confidential computing easier to adopt.

Innovation Matrix Assessment

Innovation Velocity 6/10

Advanced cryptography (functional/searchable encryption) is productised, but pace of recent releases was not independently verified.

Operational Value 5/10

Lets teams analyse or share sensitive data without exposing plaintext, reducing breach and compliance exposure.

Market Momentum 4/10

€4.2M round and Intel/Denodo partnerships, but small scale and no recent round confirmed.

Category Disruption 6/10

Protecting data in use is structurally different from perimeter or at-rest encryption.

Real-World Efficacy 4/10

No named incidents or independent tests found.

Enduring Relevance 7/10

Privacy-preserving computation grows with AI and data-sharing regulation.

Why CISOs Should Care

Data sharing and AI workloads create demand for protecting data in use without trusting every processor.

What Makes It Different

Applies functional encryption and confidential computing so computation happens on data that stays protected.

The Matrix Verdict

53/100 — INCREMENTAL INNOVATOR

Cosmian is an Incremental Innovator: strong technical idea with modest momentum and limited evidence of production efficacy.

Editorial Note: Claims vs. Verified Findings

Privacy and capability claims are vendor-described; the funding round is confirmed by press release and Silicon Canals. Total-funding figures conflict across aggregators.

Sources