Creators of FHE Studio

The User Fiendly Open-Source Fully Homomorphic Encryption IDE

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Build Privacy-Preserving AI

Train and Deploy AI Models on Encrypted Data

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Zero-Knowledge Proofs

Verifiable Computations Without Revealing Secrets

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Artifirm & FHE Studio

Projects

Artifirm was founded in 2020 as a software development company for Web, Mobile, IoT, security, blockchain, and AI areas.

Full Stack Software Development
AI: ML, NLP, Reinforcment Learning
Blockchain Development
Encrypted Computations and Private Data Sharing
Cryptography Research for Distributed Networks

Privacy-Preserving Technologies

Encrypted AI Development

Build and train AI models on encrypted data. FHE Studio enables privacy-preserving machine learning without compromising data security.

Private AI Training

Train AI models on sensitive data while keeping it encrypted. Enable collaborative learning without exposing private information.

Zero-Knowledge Proofs

Implement verifiable computations using ZKP technology. Prove the correctness of AI operations without revealing the underlying data.

Encrypted Model Inference

Deploy AI models that process encrypted inputs and produce encrypted predictions, ensuring end-to-end privacy in AI applications.

Private Data Sharing

Share sensitive data securely for AI training and inference. Enable collaborative AI development while protecting proprietary information.

Verifiable AI

Combine FHE and ZKP to create verifiable AI systems. Prove model behavior and results while keeping data and models private.

Why Choose FHE Studio for AI Development?

Privacy-First AI Development

Train AI models on sensitive data while keeping it fully encrypted. FHE Studio enables you to develop machine learning solutions without ever exposing the underlying data in plaintext.

Verifiable AI with ZKP

Implement Zero-Knowledge Proofs to create verifiable AI systems. Prove the correctness of your model's computations without revealing sensitive information about the data or model architecture.

Collaborative AI Development

Enable secure multi-party computation for AI training. Different parties can contribute encrypted data to train shared models while keeping their data private and compliant with regulations.