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53 lines
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53 lines
1.5 KiB
Plaintext
---
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title: Lux FHE Documentation
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description: Fully Homomorphic Encryption for Everyone
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---
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# Lux FHE
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**Compute on encrypted data without ever decrypting it.**
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Lux FHE is an open-source ecosystem for building privacy-preserving applications using Fully Homomorphic Encryption.
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## What is FHE?
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Fully Homomorphic Encryption allows computations on encrypted data. The server performing the computation never sees the plaintext data.
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```python
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from luxfhe import Client, Server
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# Client encrypts sensitive data
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client = Client()
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encrypted_data = client.encrypt(sensitive_value)
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# Server computes on encrypted data
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server = Server(client.evaluation_key)
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result = server.add(encrypted_data, encrypted_other)
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# Client decrypts result
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plaintext_result = client.decrypt(result)
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# Server NEVER saw sensitive_value!
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```
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## Use Cases
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### Private Machine Learning
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Train and run models on encrypted data. Patient records, financial data, and sensitive information stay encrypted throughout.
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### Private Agents
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AI agents operate on encrypted context. Your personal data never leaves your control.
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### Confidential Computing
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Execute business logic on encrypted inputs. Trade secrets and competitive data stay private.
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### Private Smart Contracts
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Blockchain applications with encrypted state. Balances, votes, and bids remain confidential.
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## Quick Links
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- [Getting Started →](/guides/quickstart)
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- [Installation →](/guides/installation)
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- [Concepts →](/concepts/what-is-fhe)
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- [API Reference →](/api/python)
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- [Examples →](https://github.com/luxfhe/examples)
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