Benchmarks and Case Studies

This page is intentionally modest.

It is not trying to prove that indexbind wins every search benchmark. It is here to show:

what a reproducible local baseline currently looks like
how large the current docs corpus is
which in-house usage patterns already rely on indexbind

Indicative Local Baseline

These measurements were captured locally on a Darwin x86_64 development machine using the current docs/site corpus and the hashing embedding backend.

Treat them as indicative rather than universal. Hardware, Rust target cache state, document shape, embedding backend, and reranking choices all affect the numbers.

Docs Site Baseline

Corpus shape:

14 markdown documents
74 chunks
hashing backend
native SQLite artifact

Observed local baseline:

Metric	Value
Build command	`npx indexbind build docs/site <tmp>/docs-site.sqlite --backend hashing`
Build time	`0.07s`
Artifact size	`352 KB`
Query sample	25 local Node searches with `mode: 'hybrid'` and `heuristic-v1` reranking
Average query latency	`3.61 ms`
Min / max query latency	`2.51 ms` / `5.28 ms`

This is the current "small real corpus" baseline for the project's own documentation set.

Regression Fixture Baseline

The bundled regression fixture is intentionally tiny and should be read as a correctness baseline, not a throughput benchmark.

Fixture shape:

3 documents
6 chunks
fixed query set in fixtures/benchmark/basic/queries.json

Observed local baseline:

Metric	Value
Build + benchmark command	`npm run benchmark:basic`
Benchmark result	`3 / 3` expected top hits passed
End-to-end benchmark run time	`0.01s` for the benchmark step after artifact build

This fixture is useful for regression detection, CI confidence, and release checks. It is not meant to stand in for a large-corpus performance claim.

Current In-House Case Studies

Current usage is still mostly first-party. That is fine at this stage, but it is worth stating plainly.

Documentation Site

indexbind powers its own documentation story:

docs are a fixed markdown corpus
the corpus can be built into retrieval artifacts during publish
the host site still owns navigation, rendering, and information architecture

This is the clearest public example of the docs-site/browser bundle path.

Blog and Publishing Flow

indexbind is also used in a blog-style publishing flow where the host system owns:

frontmatter and canonical URL decisions
content routing
product-level ranking policy

This is the clearest in-house example of the programmatic build path.

Local Knowledge Base and Workspace Search

The project is also being used in a workspace-style local knowledge-base setting where:

incremental updates matter
agent or hook-triggered refreshes matter
the host wants a local retrieval layer rather than a full mutable local-store product

This is the clearest in-house example of the incremental cache plus local Node artifact path.

How to Read These Results

The benchmark section is a local baseline, not a universal promise.
The case-study section shows the product boundary indexbind is optimized for.
The strongest current story is still "embedded retrieval for host-controlled systems", not "drop-in search for every environment".

If you want concrete wiring examples, continue to Adoption Examples.