diff --git a/README.md b/README.md
index cd5ae40..04a053a 100644
--- a/README.md
+++ b/README.md
@@ -6,10 +6,70 @@
 [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE-MIT)
 [![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](LICENSE-APACHE)
 
-Instance Distance is a fast pure-Rust implementation of the
-[Hierarchical Navigable Small Worlds paper][paper] by Malkov and Yashunin
-for finding approximate nearest neighbors. This implementation will power the
+Instance Distance is a fast pure-Rust implementation of the [Hierarchical
+Navigable Small Worlds paper][paper] by Malkov and Yashunin for finding
+approximate nearest neighbors. This implementation powers the
 [InstantDomainSearch.com][ids] backend services used for word vector indexing.
 
+## What it does
+
+Instant Distance is an implementation of a fast approximate nearest neighbor
+search algorithm. The algorithm is used to find the closest point(s) to a given
+point in a set.
+
+## Using the library
+
+### Rust
+
+```toml
+[dependencies]
+instant-segment = "0.5.0"
+```
+
+## Example
+
+```rust
+use instant_distance::{Builder, Search};
+
+fn main() {
+    let points = vec![Point(255, 0, 0), Point(255, 0, 0), Point(255, 0, 0)];
+    let values = vec!["red", "green", "blue"];
+
+    let map = Builder::default().build(points, values);
+    let mut search = Search::default();
+
+    let cambridge_blue = Point(163, 193, 173);
+
+    let closest_point = map.search(&cambridge_blue, &mut search).next().unwrap();
+
+    println!("{:?}", closest_point.value);
+}
+
+#[derive(Clone, Copy, Debug)]
+struct Point(isize, isize, isize);
+
+impl instant_distance::Point for Point {
+    fn distance(&self, other: &Self) -> f32 {
+        // Euclidean distance metric
+        (((self.0 - other.0).pow(2) + (self.1 - other.1).pow(2) + (self.2 - other.2).pow(2)) as f32)
+            .sqrt()
+    }
+}
+```
+
+## Testing
+
+Rust:
+
+```
+cargo t -p instant-distance --all-features
+```
+
+Python:
+
+```
+make test-python
+```
+
 [paper]: https://arxiv.org/abs/1603.09320
 [ids]: https://instantdomainsearch.com/
diff --git a/instant-distance/examples/colors.rs b/instant-distance/examples/colors.rs
new file mode 100644
index 0000000..776347a
--- /dev/null
+++ b/instant-distance/examples/colors.rs
@@ -0,0 +1,26 @@
+use instant_distance::{Builder, Search};
+
+fn main() {
+    let points = vec![Point(255, 0, 0), Point(0, 255, 0), Point(0, 0, 255)];
+    let values = vec!["red", "green", "blue"];
+
+    let map = Builder::default().build(points, values);
+    let mut search = Search::default();
+
+    let burnt_orange = Point(204, 85, 0);
+
+    let closest_point = map.search(&burnt_orange, &mut search).next().unwrap();
+
+    println!("{:?}", closest_point.value);
+}
+
+#[derive(Clone, Copy, Debug)]
+struct Point(isize, isize, isize);
+
+impl instant_distance::Point for Point {
+    fn distance(&self, other: &Self) -> f32 {
+        // Euclidean distance metric
+        (((self.0 - other.0).pow(2) + (self.1 - other.1).pow(2) + (self.2 - other.2).pow(2)) as f32)
+            .sqrt()
+    }
+}