From 41eadf6fd96a3de54e925a702aa7e09b911ab91e Mon Sep 17 00:00:00 2001
From: Jai <jaichopra@gmail.com>
Date: Wed, 26 Apr 2023 10:18:31 -0700
Subject: [PATCH] Update s3_lambda.md

---
 docs/src/examples/s3_lambda.md | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/docs/src/examples/s3_lambda.md b/docs/src/examples/s3_lambda.md
index 46cb6c53..59218686 100644
--- a/docs/src/examples/s3_lambda.md
+++ b/docs/src/examples/s3_lambda.md
@@ -2,6 +2,8 @@
 
 ## Store your data on S3 and use Lambda to compute embeddings and retrieve queries in production easily.
 
+## <img id="splash" width="1239" alt="s3-lambda" src="https://user-images.githubusercontent.com/917119/234653050-305a1e90-9305-40ab-b014-c823172a948c.png">
+
 This is a great option if you're wanting to scale with your use case and save effort and costs of maintenance.
 
 Let's walk through how to get a simple Lambda function that queries the SIFT dataset on S3.
@@ -69,4 +71,4 @@ def handler(event, context):
             "Content-Type": "application/json"
         },
         "body": rs.to_pandas().to_json()
-    }```
\ No newline at end of file
+    }```