diff --git a/website/meta/universe.json b/website/meta/universe.json
index b39ebb528..e36ba5676 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -2837,6 +2837,56 @@
             "tags": ["coreference", "multi-lingual", "cross-lingual", "allennlp"],
             "spacy_version": 3
         },
+        {
+            "id": "adeptaugmentations",
+            "title": "Adept Augmentations",
+            "slogan": " A Python library aimed at dissecting and augmenting NER training data for a few-shot scenario.",
+            "description": "EntitySwapAugmenter takes either a `datasets.Dataset` or a `spacy.tokens.DocBin`. Additionally, it is optional to provide a set of labels. It initially creates a knowledge base of entities belonging to a certain label. When running `augmenter.augment()` for N runs, it then creates N new sentences with random swaps of the original entities with an entity of the same corresponding label from the knowledge base.\n\nFor example, assuming that we have knowledge base for `PERSONS`, `LOCATIONS` and `PRODUCTS`. We can then create additional data for the sentence \"Momofuko Ando created instant noodles in Osaka.\" using `augmenter.augment(N=2)`, resulting in \"David created instant noodles in Madrid.\" or \"Tom created Adept Augmentations in the Netherlands\".",
+            "github": "davidberenstein1957/adept-augmentations",
+            "pip": "adept-augmentations",
+            "thumb": "https://raw.githubusercontent.com/Pandora-Intelligence/crosslingual-coreference/master/img/logo.png",
+            "code_example": [
+                "import spacy",
+                "from spacy.tokens import DocBin",
+                "",
+                "from adept_augmentations import EntitySwapAugmenter",
+                "",
+                "nlp = spacy.load(\"en_core_web_sm\")",
+                "",
+                "TRAIN_DATA = [",
+                "    \"Apple is looking at buying U.K. startup for $1 billion\",",
+                "    \"Microsoft acquires GitHub for $7.5 billion\"",
+                "]",
+                "docs = nlp.pipe(TRAIN_DATA)",
+                "",
+                "# Create a new DocBin",
+                "doc_bin = DocBin(docs=docs)",
+                "",
+                "# Augment Data",
+                "doc_bin = EntitySwapAugmenter(doc_bin).augment(4)",
+                "for doc in doc_bin.get_docs(nlp.vocab):",
+                "    print(doc.text)",
+                "",
+                "# Output",
+                "#",
+                "# GitHub is looking at buying U.K. startup for $ 7.5 billion",
+                "# Microsoft is looking at buying U.K. startup for $ 1 billion",
+                "# Microsoft is looking at buying U.K. startup for $ 7.5 billion",
+                "# GitHub is looking at buying U.K. startup for $ 1 billion",
+                "# Microsoft acquires Apple for $ 7.5 billion",
+                "# Apple acquires Microsoft for $ 1 billion",
+                "# Microsoft acquires Microsoft for $ 7.5 billion",
+                "# GitHub acquires GitHub for $ 1 billion"
+            ],
+            "author": "David Berenstein",
+            "author_links": {
+                "github": "davidberenstein1957",
+                "website": "https://www.linkedin.com/in/david-berenstein-1bab11105/"
+            },
+            "category": ["standalone"],
+            "tags": ["ner", "few-shot", "augmentation", "datasets", "training"],
+            "spacy_version": 3
+        },
         {
             "id": "blackstone",
             "title": "Blackstone",