Stoffel develops tools and infrastructure for secure multi-party computation (MPC) that enable developers to build privacy-preserving applications without requiring cryptography expertise. The company provides a suite of products including Stoffel Lang (a programming language for MPC), Stoffel VM (a virtual machine for executing MPC protocols), and SDKs that abstract the complexity of cryptographic implementations. The platform addresses the challenge of building applications that can perform computations on sensitive data without exposing the underlying information to any single party. Their technology allows multiple parties to jointly compute functions over their inputs while keeping those inputs private, enabling use cases such as federated learning aggregation and distributed key generation for MPC wallets. Stoffel's approach focuses on making MPC accessible to mainstream developers by providing developer-friendly tooling rather than requiring deep cryptographic knowledge. The team has experience building production systems at scale, with backgrounds in distributed systems, virtual machine design, cryptographic protocol implementation, and developer tooling. The company targets developers building privacy-first applications across various domains where data confidentiality is critical. Their solutions are designed to bridge the gap between academic cryptographic research and practical, production-ready implementations that can be deployed in real-world systems.