> For the complete documentation index, see [llms.txt](https://docs.envector.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.envector.io/1.4.x/core-concepts/fhe.md).

# Homomorphic Encryption

Homomorphic Encryption (HE) enables computation on encrypted data. enVector leverages HE so the server can compute similarity without decrypting vectors.

## What It Enables

* Compute Inner Product (IP) over encrypted vectors.
* Keep data encrypted at rest, in transit, and during use.
* Allow zero-trust processing: the server operates without plaintext access.

## Practical Considerations

* Performance: HE is computationally heavier than plaintext. Use batching and dimension planning for best results.
* Precision: Real-number HE schemes support approximate arithmetic suitable for vector similarity.
* Keys: Clients manage secret keys; servers use shared public/evaluation keys for computation.

## When To Use Encrypted Queries

* Important: The system currently places the highest value on protecting the DB itself, so ciphertext queries are not supported. Only plaintext queries are available.
* Plaintext queries are acceptable if the query content is non-sensitive and you want lower latency.


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