Stoffel is a development platform that enables applications to process encrypted data without decryption through secure multi-party computation (MPC). The platform consists of three main components: Stoffel-Lang for defining privacy-preserving logic, StoffelVM for executing computations on encrypted inputs, and application SDKs for integration. The platform allows developers to build applications where raw user data remains encrypted throughout the entire computation lifecycle. Data is encrypted at rest on user devices, remains encrypted during transit, and stays encrypted during processing. The system uses cryptographic protocols to ensure that no single party, including the application developer, can access raw input data. Stoffel supports use cases including federated learning aggregation for AI/ML model training, distributed key generation for key management, and private analytics. The platform includes a domain-specific language (Stoffel-Lang) that treats data leakage as a compile-time error rather than a runtime concern. The development environment includes local simulation capabilities for testing with multiple parties, compilation to optimized VM bytecode, and SDKs for Python, Rust, and Solidity. The architecture is designed for self-hosting, allowing organizations to deploy the entire stack within their own infrastructure. The platform provides cryptographic proof of privacy guarantees through its architecture rather than relying on policy-based assurances. All components are available as open-source repositories on GitHub.