qdrant · mwitiderrick · Jul 1, 2025 · Jul 1, 2025 · Jul 1, 2025 · Jul 2, 2025
diff --git a/qdrant-landing/content/documentation/examples/_index.md b/qdrant-landing/content/documentation/examples/_index.md
@@ -19,6 +19,8 @@ partition: build
 | [Movie Recommendation System](/documentation/examples/recommendation-system-ovhcloud/)                                 | Build a Movie Recommendation System with LlamaIndex and With JinaAI             | Qdrant |
 | [GraphRAG Agent](/documentation/examples/graphrag-qdrant-neo4j/)                                 | Build a GraphRAG Agent with Neo4J and Qdrant               | Qdrant, Neo4j |
 | [Building a Chain-of-Thought Medical Chatbot with Qdrant and DSPy](/documentation/examples/Qdrant-DSPy-medicalbot/)                                 | How to build a medical chatbot grounded in medical literature with Qdrant and DSPy.              | Qdrant, DSPy |
+| [Question Answering as a Service with Cohere and Qdrant](/documentation/examples/qa-with-cohere-and-qdrant/)                                 | How to build a Question Answering System With Cohere and Qdrant.              | Qdrant, Cohere |
+
 
 
 

diff --git a/...ent/articles/qa-with-cohere-and-qdrant.md → ...ion/examples/qa-with-cohere-and-qdrant.md b/...ent/articles/qa-with-cohere-and-qdrant.md → ...ion/examples/qa-with-cohere-and-qdrant.md
@@ -1,23 +1,10 @@
 ---
 title: Question Answering as a Service with Cohere and Qdrant
-short_description: "End-to-end Question Answering system for the biomedical data with SaaS tools: Cohere co.embed API and Qdrant"
-description: "End-to-end Question Answering system for the biomedical data with SaaS tools: Cohere co.embed API and Qdrant"
-social_preview_image: /articles_data/qa-with-cohere-and-qdrant/social_preview.png
-small_preview_image: /articles_data/qa-with-cohere-and-qdrant/q-and-a-article-icon.svg
-preview_dir: /articles_data/qa-with-cohere-and-qdrant/preview
-weight: 7
-author: Kacper Łukawski
-author_link: https://medium.com/@lukawskikacper
-date: 2022-11-29T15:45:00+01:00
-draft: false
-keywords:
-  - vector search
-  - question answering
-  - cohere
-  - co.embed
-  - embeddings
-category: practicle-examples
+weight: 19
+aliases:
+    - /articles/qa-with-cohere-and-qdrant/
 ---
+# Question Answering as a Service with Cohere and Qdrant
 
 Bi-encoders are probably the most efficient way of setting up a semantic Question Answering system. 
 This architecture relies on the same neural model that creates vector embeddings for both questions and answers. 

diff --git a/...nt-landing/static/articles_data/qa-with-cohere-and-qdrant/biencoder-diagram.png b/...nt-landing/static/articles_data/qa-with-cohere-and-qdrant/biencoder-diagram.png
diff --git a/.../static/articles_data/qa-with-cohere-and-qdrant/search-with-vector-database.png b/.../static/articles_data/qa-with-cohere-and-qdrant/search-with-vector-database.png
diff --git a/qdrant-landing/static/articles_data/qa-with-cohere-and-qdrant/vector-database.png b/qdrant-landing/static/articles_data/qa-with-cohere-and-qdrant/vector-database.png