Search the site

Browse the documentation, the product pages and the engineering log. The keywords below lead straight to the matching sections.

A semantic search

Site search runs on Vela. Your query is turned into a vector, then compared against the indexed pages.

Results are ranked by similarity rather than exact word matching. A query written in plain language therefore returns the relevant pages, even with no shared term.

Natural-language queries
Ranking by similarity
Filters by site section
148
Pages indexed
12
Site sections
8
Languages covered

Search suggestions

The terms most often used to query the site, grouped by topic.

Embeddings

The format of vectors sent to Vela, accepted dimensions and compatible models.

  • Dimensions
  • Normalization
  • Compatible models

Indexes

Available index structures, build parameters and the trade-off between recall and latency.

  • HNSW
  • IVF
  • Quantization

k-NN

Nearest-neighbour queries: top-k size, distance metrics and score thresholds.

  • Top-k
  • Cosine distance
  • Dot product

RAG

Retrieving context to feed a language model from your own documents.

  • Document chunking
  • Reranking
  • Source citations

Latency

Response-time budgets, percentile measurement and behaviour under load.

  • p50 and p99
  • Caching
  • Batched queries

Filters

Metadata filtering combined with the similarity computation, in a single query.

  • Metadata
  • Boolean expressions
  • Namespaces

How to query the site

Four steps to useful results, and what to do when a query returns nothing.

01

Phrase the query

A full sentence works better than a single word. The query is turned into a vector before being compared against the index.

02

Narrow the scope

A filter limits the search to the documentation, the product pages or the engineering log. It is applied before the similarity computation.

03

Read the score

Every result carries a similarity score between 0 and 1. Above 0.7, the match is generally reliable.

04

No results

If no page clears the threshold, drop the filters or rephrase the query. The shortcuts below cover the most common requests.

Frequent destinations

The most-visited pages, reachable without going through search.

Documentation

Getting started: create an index and send your first vectors

API keys, SDKs and a sample k-NN query.

docs.vela.dev

Open the page
Product

The search engine: indexes, similarity queries and filters

Index structures, measured recall and expected latency.

Up to billion-vector scale

Open the page
Pricing

Price list by volume of vectors stored

Cost per million vectors and per query.

Monthly billing, no commitment

Open the page

Indexed sections

Internal search covers the following four sections of the site.

Product

How the engine works, index structures and similarity queries.

Documentation

API reference, installation guides and annotated code samples.

Integrations

Connectors, SDKs and supported client libraries.

Engineering log

Technical articles, performance measurements and release notes.

Can't find the answer?

The documentation covers the API, the SDKs and the common use cases. For a specific question, write to support@vela.dev.