diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index e02f998..720c9ff 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -56,6 +56,7 @@ jobs:
         run: |
           poetry install --no-interaction --no-root
           poetry install --with dev 
+          poetry install --extras "spacy"
 
       - name: Run Pytest with coverage
         run: |
diff --git a/Makefile b/Makefile
index 961ea8a..dd1c236 100644
--- a/Makefile
+++ b/Makefile
@@ -10,6 +10,8 @@ test:
 coverage:
 	poetry run pytest -vvv --cov
 
+format:
+	poetry run ruff format .
 
 .PHONY: test coverage 
 
diff --git a/README.md b/README.md
index 2f0986d..cd54d98 100644
--- a/README.md
+++ b/README.md
@@ -7,17 +7,34 @@ ShadowData is a Python library designed to simplify the processing and handling
 
 ## Features (The project is under development)
 
-- Data anonymization.
-- Encryption and decryption of sensitive data.
-- Data masking for privacy-preserving data handling.
-- Easy integration with existing Python data processing pipelines.
-- Compliance with GDPR, LGPD and other data protection regulations.
+- Data anonymization. (Work in progress)
+- PII - Personal Identified Information detection using Natual Language Processing (Work in progress) 
+- Encryption and decryption of sensitive data. (Development has not started yet)
+- Data masking for privacy-preserving data handling. (Work in progress)
+- Compliance with GDPR, LGPD and other data protection regulations. (Work in progress)
 
-## Installing
-`pip install shadow_data`
+## Installation Instructions
+
+```bash
+pip install shadow_data
+```
+* Installs only the core library, without the spaCy dependency.
+
+```bash 
+pip install shadowdata[spacy]
+```
+* Installs spaCy automatically, based on your platform.
+
+By default, ShadowData will automatically download the necessary language model if it’s not already installed. However, if you’d prefer to install it manually, use the following command:
+```bash
+python -m spacy download en_core_web_trf
+```
+Make sure to run this command within your project’s virtual environment.
+
+[Check spaCy's documentation to know more about the Language Models.](https://spacy.io/models)
 
 ## Usage
-Examples soon
+There are some usage examples at the [examples](examples) directory
 
 ## Contributing
 
diff --git a/examples/anonymization.md b/examples/anonymization.md
new file mode 100644
index 0000000..97befe6
--- /dev/null
+++ b/examples/anonymization.md
@@ -0,0 +1,20 @@
+# Simple text replacement and IPV4 anonymization
+
+```python
+from shadow_data.anonymization import TextProcessor, Ipv4Anonymization
+
+original_content = 'Little John likes to play with the staff.'
+anonymized_content = TextProcessor.replace_text('Little John', 'XXXXXX XXXX', original_content)
+print(f'Original content: {original_content} | Anonymized content: {anonymized_content}')
+
+original_ip = '200.189.45.128'
+anonymized_content = Ipv4Anonymization.anonymize_ipv4(original_ip)
+print(f'Original IP: {original_ip} | Anonymized IP: {anonymized_content}')
+```
+
+### Results:
+
+```plain
+Original content: Little John likes to play with the staff. | Anonymized content: XXXXXX XXXX likes to play with the staff.
+Original IP: 200.189.45.128 | Anonymized IP: 200.X.X.X
+```
\ No newline at end of file
diff --git a/examples/i10n_brazil.md b/examples/i10n_brazil.md
new file mode 100644
index 0000000..3feb35a
--- /dev/null
+++ b/examples/i10n_brazil.md
@@ -0,0 +1,24 @@
+# Localized anonymization for Brazilian individual (CPF) and corporate (CNPJ) tax IDs.
+
+```python
+from shadow_data.l10n.brazil import IdentifierAnonymizer
+
+# Anonymize CPF
+
+cpf = '806.846.761-09'
+cpf_anonymized = IdentifierAnonymizer(cpf)
+cpf_anonymized.anonymize()
+print(f'Original CPF: {cpf} : Anonymized CPF: {cpf_anonymized.cleaned_content}')
+
+cnpj = '26.283.050/0001-17'
+cnpj_anonymized = IdentifierAnonymizer(cnpj)
+cnpj_anonymized.anonymize()
+print(f'Original CNPJ: {cnpj} : Anonymized CPF: {cnpj_anonymized.cleaned_content}')
+```
+
+### Results
+
+```plain
+Original CPF: 806.846.761-09 : Anonymized CPF: 80*********
+Original CNPJ: 26.283.050/0001-17 : Anonymized CPF: 26************
+```
diff --git a/examples/i10n_us.md b/examples/i10n_us.md
new file mode 100644
index 0000000..f019702
--- /dev/null
+++ b/examples/i10n_us.md
@@ -0,0 +1,17 @@
+# Localized anonymization for U.S. Social Security Numbers.
+
+```python
+from shadow_data.l10n.usa import IdentifierAnonymizer
+
+text_content_with_ssn = "Billy's SSN is 479-92-5042. Please make sure it's anonymized."
+anonymizer = IdentifierAnonymizer(text_content_with_ssn)
+anonymizer.anonymize()
+
+print(f'Original: {text_content_with_ssn} | Anonymized: {anonymizer.cleaned_content}')
+```
+
+### Results
+
+```plain
+Original: Billy's SSN is 479-92-5042. Please make sure it's anonymized. | Anonymized: Billy's SSN is XXX-XX-5042. Please make sure it's anonymized.
+```
\ No newline at end of file
diff --git a/examples/pii_nlp.md b/examples/pii_nlp.md
new file mode 100644
index 0000000..48e9ec4
--- /dev/null
+++ b/examples/pii_nlp.md
@@ -0,0 +1,24 @@
+# Personally Identifiable Information with Natural Language Processing
+
+PII, or Personally Identifiable Information, refers to any data that can be used to identify a specific individual. This includes names, addresses, phone numbers, social security numbers, email addresses, and other personal details that can be linked to a person. Protecting PII is essential for maintaining privacy and ensuring data security.
+
+spaCy is an open-source library for advanced natural language processing (NLP) in Python. It provides fast and efficient tools for tasks like tokenization, part-of-speech tagging, named entity recognition, and more, with support for multiple languages.
+
+This library primarily uses spaCy to process text and identify personally identifiable information (PII).
+
+**_The code sample below is in Portuguese because the results were better than those from the tests I conducted in English._**
+
+```python 
+from shadow_data.pii.enums import ModelLang, ModelCore, ModelSize
+from shadow_data.pii.spacy import SensitiveData
+
+content = 'João Silva mora na Rua das Acácias, 123, Apartamento 5B, São Paulo, SP, 01310-000. Ele trabalha como Gerente de Projetos na TechNova Soluções, uma empresa de tecnologia em crescimento localizada na Avenida Paulista, 987, São Paulo, SP, 01311-200. João está na empresa há três anos, onde lidera uma equipe de desenvolvedores e designers, garantindo que os projetos sejam entregues no prazo e atendam às expectativas dos clientes. Você pode contatá-lo pelo telefone (11) 91234-5678 ou pelo e-mail joao.silva@technova.com. João é muito respeitado por suas habilidades de liderança e resolução de problemas dentro da empresa.'
+instance = SensitiveData()
+sensitive_data = instance.identify_sensitive_data(ModelLang.PORTUGUESE, ModelCore.NEWS, ModelSize.LARGE, content)
+print(sensitive_data)
+```
+
+### Results:
+```plain
+[('João Silva', 'PER'), ('Rua das Acácias', 'LOC'), ('Apartamento 5B', 'LOC'), ('São Paulo', 'LOC'), ('SP', 'LOC'), ('Gerente de Projetos', 'MISC'), ('TechNova Soluções', 'LOC'), ('Avenida Paulista', 'LOC'), ('São Paulo', 'LOC'), ('SP', 'LOC'), ('João', 'PER'), ('joao.silva@technova.com', 'LOC'), ('João', 'PER')]
+```
\ No newline at end of file
diff --git a/poetry.lock b/poetry.lock
index 4a952fd..86289c9 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,5 +1,224 @@
 # This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
+[[package]]
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+]
+
+[[package]]
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+
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+gs = ["google-cloud-storage"]
+s3 = ["boto3 (>=1.34.0)"]
+
 [[package]]
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 version = "0.4.6"
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+optional = true
+python-versions = ">=3.6"
+files = [
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+
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -106,6 +386,351 @@ files = [
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 ]
 
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+
+[package.dependencies]
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+
+[package.extras]
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+
+[[package]]
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+
+[package.extras]
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+test = ["pytest", "pytest-cov"]
+
+[[package]]
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+optional = true
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+    {file = "wrapt-1.16.0.tar.gz", hash = "sha256:5f370f952971e7d17c7d1ead40e49f32345a7f7a5373571ef44d800d06b1899d"},
+]
+
+[extras]
+spacy = ["spacy"]
+
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.12"
-content-hash = "4174abb80dd1a6696cb4a1c5b50e984d11c1e8e3ad5c6638bb9dbd3afafb1a0f"
+content-hash = "622cdde5d1e737b2fed9468b483925a8d596c5df66eff37f75c00749d9773eab"
diff --git a/pyproject.toml b/pyproject.toml
index 6ec6482..1c426f9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -3,11 +3,16 @@ name = "shadow_data"
 version = "0.1.0"
 description = "A sensitive data handler python library"
 authors = ["Adler Medrado <adler@adlermedrado.com.br>"]
-license = "BSD-3 Clause"
+license = "MIT"
 
 [tool.poetry.dependencies]
 python = "^3.12"
 
+spacy = { version = "^3.8", optional = true, markers = "platform_system == 'Darwin' and platform_machine == 'arm64' or platform_system == 'Darwin' and platform_machine == 'x86_64' or platform_system == 'Linux' or platform_system == 'Windows'" }
+python-json-logger = "^2.0.7"
+
+[tool.poetry.extras]
+spacy = ["spacy"]
 
 [tool.poetry.group.dev.dependencies]
 ruff = "^0.6.8"
diff --git a/pytest.ini b/pytest.ini
new file mode 100644
index 0000000..36ba433
--- /dev/null
+++ b/pytest.ini
@@ -0,0 +1,3 @@
+[pytest]
+addopts = -v --maxfail=3 --disable-warnings
+testpaths = tests
\ No newline at end of file
diff --git a/shadow_data/anonymization.py b/shadow_data/anonymization.py
index 1b1b4e3..c00b7a2 100644
--- a/shadow_data/anonymization.py
+++ b/shadow_data/anonymization.py
@@ -1,5 +1,6 @@
 import re
 
+
 class TextProcessor:
     @staticmethod
     def replace_text(original_term: str, to_replace: str, original_content: str) -> str:
@@ -8,5 +9,5 @@ def replace_text(original_term: str, to_replace: str, original_content: str) ->
 
 class Ipv4Anonymization:
     @staticmethod
-    def anonymize_ipv4(text: str, pattern: str = r"\1.X.X.X") -> str:
-        return TextProcessor.replace_text(r"\b(\d{1,3})(\.\d{1,3}){3}\b", pattern, text)
+    def anonymize_ipv4(text: str, pattern: str = r'\1.X.X.X') -> str:
+        return TextProcessor.replace_text(r'\b(\d{1,3})(\.\d{1,3}){3}\b', pattern, text)
diff --git a/shadow_data/l10n/ClearIdentifier.py b/shadow_data/l10n/ClearIdentifier.py
new file mode 100644
index 0000000..c06015e
--- /dev/null
+++ b/shadow_data/l10n/ClearIdentifier.py
@@ -0,0 +1,12 @@
+from abc import ABC, abstractmethod
+
+
+class ClearIdentifier(ABC):
+    cleaned_content: str
+
+    def __init__(self, content_to_anonymize):
+        self.content_to_anonymize = content_to_anonymize
+
+    @abstractmethod
+    def anonymize(self):
+        pass
diff --git a/shadow_data/l10n/brazil.py b/shadow_data/l10n/brazil.py
new file mode 100644
index 0000000..85b5ecf
--- /dev/null
+++ b/shadow_data/l10n/brazil.py
@@ -0,0 +1,20 @@
+from shadow_data.anonymization import TextProcessor
+from shadow_data.l10n.ClearIdentifier import ClearIdentifier
+from shadow_data.utils import only_digits
+
+
+class IdentifierAnonymizer(ClearIdentifier):
+    def anonymize(self):
+        clean_identifier = only_digits(self.content_to_anonymize)
+        if len(clean_identifier) == 11:  # CPF
+            return self._anonymize_cpf(clean_identifier)
+        elif len(clean_identifier) == 14:  # CNPJ
+            return self._anonymize_cnpj(clean_identifier)
+        else:
+            raise ValueError('Invalid identifier length')
+
+    def _anonymize_cpf(self, content: str):
+        self.cleaned_content = TextProcessor.replace_text(r'(\d{2})(\d{9})', r'\1*********', content)
+
+    def _anonymize_cnpj(self, content: str):
+        self.cleaned_content = TextProcessor.replace_text(r'(\d{2})(\d{12})', r'\1************', content)
diff --git a/shadow_data/l10n/brazilian.py b/shadow_data/l10n/brazilian.py
deleted file mode 100644
index 7dc2a35..0000000
--- a/shadow_data/l10n/brazilian.py
+++ /dev/null
@@ -1,21 +0,0 @@
-from shadow_data.anonymization import TextProcessor
-from shadow_data.utils import only_digits
-
-class IdentifierAnonymizer:
-    def __init__(self, identifier: str):
-        self.identifier = identifier
-        self.clean_identifier = only_digits(identifier)
-
-    def anonymize(self) -> str:
-        if len(self.clean_identifier) == 11:  # CPF
-            return self._anonymize_cpf()
-        elif len(self.clean_identifier) == 14:  # CNPJ
-            return self._anonymize_cnpj()
-        else:
-            raise ValueError("Invalid identifier length")
-
-    def _anonymize_cpf(self) -> str:
-        return TextProcessor.replace_text(r"(\d{2})(\d{9})", r"\1*********", self.clean_identifier)
-
-    def _anonymize_cnpj(self) -> str:
-        return TextProcessor.replace_text(r"(\d{2})(\d{12})", r"\1************", self.clean_identifier)
diff --git a/shadow_data/l10n/usa.py b/shadow_data/l10n/usa.py
new file mode 100644
index 0000000..d960b1c
--- /dev/null
+++ b/shadow_data/l10n/usa.py
@@ -0,0 +1,9 @@
+import re
+
+from shadow_data.l10n.ClearIdentifier import ClearIdentifier
+
+
+class IdentifierAnonymizer(ClearIdentifier):
+    def anonymize(self):
+        ssn_pattern = r'\b(\d{3})-(\d{2})-(\d{4})\b'
+        self.cleaned_content = re.sub(ssn_pattern, r'XXX-XX-\3', self.content_to_anonymize)
diff --git a/shadow_data/pii/__init__.py b/shadow_data/pii/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/shadow_data/pii/enums.py b/shadow_data/pii/enums.py
new file mode 100644
index 0000000..faf9e71
--- /dev/null
+++ b/shadow_data/pii/enums.py
@@ -0,0 +1,21 @@
+from enum import Enum
+
+
+class ModelSize(Enum):
+    SMALL = 'sm'
+    MEDIUM = 'md'
+    LARGE = 'lg'
+    TRF = 'trf'
+
+
+class ModelLang(Enum):
+    ENGLISH = 'en'
+    PORTUGUESE = 'pt'
+    SPANISH = 'es'
+    GERMAN = 'de'
+    FRENCH = 'fr'
+
+
+class ModelCore(Enum):
+    NEWS = 'core_news'
+    WEB = 'core_web'
diff --git a/shadow_data/pii/spacy.py b/shadow_data/pii/spacy.py
new file mode 100644
index 0000000..e14243a
--- /dev/null
+++ b/shadow_data/pii/spacy.py
@@ -0,0 +1,62 @@
+import spacy
+import subprocess
+
+from spacy.language import Language
+
+from shadow_data.pii.enums import ModelLang, ModelCore, ModelSize
+
+
+class ModelSelector:
+    @staticmethod
+    def select(lang: ModelLang, core: ModelCore, size: ModelSize) -> Language:
+        """
+        Loads a spaCy model by combining language, core news, and size.
+
+        Parameters:
+        - lang (ModelLang): The language model.
+        - core (ModelCoreNews): The core news model.
+        - size (ModelSize): The size of the model.
+
+        Returns:
+        - nlp: The loaded spaCy model.
+
+        Raises:
+        - TypeError: If any of the parameters are not of the expected type.
+        """
+        if not isinstance(lang, ModelLang):
+            raise TypeError(f'Expected lang to be an instance of ModelLang, got {type(lang).__name__}')
+        if not isinstance(core, ModelCore):
+            raise TypeError(f'Expected core to be an instance of ModelCoreNews, got {type(core).__name__}')
+        if not isinstance(size, ModelSize):
+            raise TypeError(f'Expected size to be an instance of ModelSize, got {type(size).__name__}')
+
+        model_name = f'{lang.value}_{core.value}_{size.value}'
+        try:
+            nlp = spacy.load(model_name)
+        except OSError:
+            try:
+                subprocess.run(['python', '-m', 'spacy', 'download', model_name], check=True)
+                nlp = spacy.load(model_name)
+            except subprocess.CalledProcessError:
+                raise RuntimeError(f'Could not download and load model {model_name}')
+        return nlp
+
+
+class SensitiveData:
+    def set_model(self, model_lang: ModelLang, model_core: ModelCore, model_size: ModelSize) -> Language:
+        model_selector = ModelSelector()
+        return model_selector.select(model_lang, model_core, model_size)
+
+    def identify_sensitive_data(
+        self, model_lang: ModelLang, model_core: ModelCore, model_size: ModelSize, content
+    ) -> list:
+        nlp = self.set_model(model_lang, model_core, model_size)
+        doc = nlp(content)
+
+        sensitive_data = []
+
+        for ent in doc.ents:
+            if ent.label_ in ['PER', 'LOC', 'ORG', 'MISC']:
+                sensitive_data.append((ent.text, ent.label_))
+
+        return sensitive_data
diff --git a/shadow_data/utils.py b/shadow_data/utils.py
index 6d10af2..3e1b5b2 100644
--- a/shadow_data/utils.py
+++ b/shadow_data/utils.py
@@ -2,4 +2,4 @@
 
 
 def only_digits(content: str) -> str:
-    return re.sub(r"\D", "", content)
+    return re.sub(r'\D', '', content)
diff --git a/tests/i10n/test_brazil.py b/tests/i10n/test_brazil.py
new file mode 100644
index 0000000..2bd3833
--- /dev/null
+++ b/tests/i10n/test_brazil.py
@@ -0,0 +1,25 @@
+import pytest
+
+from shadow_data.l10n.brazil import IdentifierAnonymizer
+
+
+class TestIdentifierAnonymizer:
+    def test_anonymize_valid_cpf(self):
+        identifier_anonymizer = IdentifierAnonymizer('123.456.789-09')
+        identifier_anonymizer.anonymize()
+        assert identifier_anonymizer.cleaned_content == '12*********'
+
+    def test_anonymize_valid_cnpj(self):
+        identifier_anonymizer = IdentifierAnonymizer('12.345.678/0001-95')
+        identifier_anonymizer.anonymize()
+        assert identifier_anonymizer.cleaned_content == '12************'
+
+    def test_invalid_identifier_short_length(self):
+        with pytest.raises(ValueError):
+            identifier_anonymizer = IdentifierAnonymizer('123456789')
+            identifier_anonymizer.anonymize()
+
+    def test_invalid_identifier_long_length(self):
+        with pytest.raises(ValueError):
+            identifier_anonymizer = IdentifierAnonymizer('123456789012345')
+            identifier_anonymizer.anonymize()
diff --git a/tests/i10n/test_brazilian.py b/tests/i10n/test_brazilian.py
deleted file mode 100644
index 2d2c3b9..0000000
--- a/tests/i10n/test_brazilian.py
+++ /dev/null
@@ -1,25 +0,0 @@
-import pytest
-
-from shadow_data.l10n.brazilian import IdentifierAnonymizer
-
-
-def test_anonymize_valid_cpf():
-    identifier_anonymizer = IdentifierAnonymizer("123.456.789-09")
-    assert identifier_anonymizer.anonymize() == "12*********"
-
-
-def test_anonymize_valid_cnpj():
-    identifier_anonymizer = IdentifierAnonymizer("12.345.678/0001-95")
-    assert identifier_anonymizer.anonymize() == "12************"
-
-
-def test_invalid_identifier_short_length():
-    with pytest.raises(ValueError):
-        identifier_anonymizer = IdentifierAnonymizer("123456789")
-        identifier_anonymizer.anonymize()
-
-
-def test_invalid_identifier_long_length():
-    with pytest.raises(ValueError):
-        identifier_anonymizer = IdentifierAnonymizer("123456789012345")
-        identifier_anonymizer.anonymize()
diff --git a/tests/i10n/test_clear_identifier.py b/tests/i10n/test_clear_identifier.py
new file mode 100644
index 0000000..5403069
--- /dev/null
+++ b/tests/i10n/test_clear_identifier.py
@@ -0,0 +1,16 @@
+import pytest
+from shadow_data.l10n.ClearIdentifier import ClearIdentifier
+
+
+class TestClearIdentifier:
+    def test_abstract_method_not_implemented(self):
+        with pytest.raises(TypeError):
+            ClearIdentifier('test')
+
+    def test_anonymize_not_implemented(self):
+        class IncompleteIdentifier(ClearIdentifier):
+            def anonymize(self):
+                super().anonymize()
+
+        instance = IncompleteIdentifier('test')
+        instance.anonymize()
diff --git a/tests/i10n/test_usa.py b/tests/i10n/test_usa.py
new file mode 100644
index 0000000..3678a33
--- /dev/null
+++ b/tests/i10n/test_usa.py
@@ -0,0 +1,38 @@
+from shadow_data.l10n.usa import IdentifierAnonymizer
+
+
+class TestIdentifierAnonymizer:
+    def test_anonymize_ssn(self):
+        content = 'My SSN is 123-45-6789.'
+        expected_output = 'My SSN is XXX-XX-6789.'
+        anonymizer = IdentifierAnonymizer(content)
+        anonymizer.anonymize()
+        assert anonymizer.cleaned_content == expected_output
+
+    def test_anonymize_multiple_ssns(self):
+        content = 'SSNs are 123-45-6789 and 987-65-4321.'
+        expected_output = 'SSNs are XXX-XX-6789 and XXX-XX-4321.'
+        anonymizer = IdentifierAnonymizer(content)
+        anonymizer.anonymize()
+        assert anonymizer.cleaned_content == expected_output
+
+    def test_anonymize_no_ssn(self):
+        content = 'There is no SSN here.'
+        expected_output = 'There is no SSN here.'
+        anonymizer = IdentifierAnonymizer(content)
+        anonymizer.anonymize()
+        assert anonymizer.cleaned_content == expected_output
+
+    def test_anonymize_partial_ssn(self):
+        content = 'Partial SSN 123-45 is not complete.'
+        expected_output = 'Partial SSN 123-45 is not complete.'
+        anonymizer = IdentifierAnonymizer(content)
+        anonymizer.anonymize()
+        assert anonymizer.cleaned_content == expected_output
+
+    def test_anonymize_invalid_ssn_format(self):
+        content = 'Invalid SSN 1234-56-7890.'
+        expected_output = 'Invalid SSN 1234-56-7890.'
+        anonymizer = IdentifierAnonymizer(content)
+        anonymizer.anonymize()
+        assert anonymizer.cleaned_content == expected_output
diff --git a/tests/pii/__init__.py b/tests/pii/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/pii/test_pii_spacy.py b/tests/pii/test_pii_spacy.py
new file mode 100644
index 0000000..4cbdb93
--- /dev/null
+++ b/tests/pii/test_pii_spacy.py
@@ -0,0 +1,157 @@
+import pytest
+from unittest.mock import patch, MagicMock
+
+from spacy import Language
+
+from shadow_data.pii.enums import ModelLang, ModelCore, ModelSize
+from shadow_data.pii.spacy import ModelSelector, SensitiveData
+import subprocess
+
+
+class TestModelSelector:
+    def test_select_valid_model(self):
+        with patch('spacy.load') as mock_spacy_load:
+            mock_spacy_load.return_value = MagicMock()
+
+            lang = ModelLang.ENGLISH
+            core = ModelCore.NEWS
+            size = ModelSize.SMALL
+
+            nlp = ModelSelector.select(lang, core, size)
+
+            mock_spacy_load.assert_called_once_with('en_core_news_sm')
+            assert isinstance(nlp, MagicMock)
+
+    def test_select_invalid_lang_type(self):
+        core = ModelCore.NEWS
+        size = ModelSize
+
+        with pytest.raises(TypeError):
+            ModelSelector.select('en', core, size)
+
+    def test_select_invalid_core_type(self):
+        lang = ModelLang.ENGLISH
+        size = ModelSize.SMALL
+
+        with pytest.raises(TypeError):
+            ModelSelector.select(lang, 'core', size)
+
+    def test_select_invalid_size_type(self):
+        lang = ModelLang.ENGLISH
+        core = ModelCore.NEWS
+
+        with pytest.raises(TypeError):
+            ModelSelector.select(lang, core, 'big')
+
+    def test_select_model_download(self):
+        with patch('spacy.load') as mock_spacy_load, patch('subprocess.run') as mock_subprocess_run:
+            mock_spacy_load.side_effect = [OSError, MagicMock()]
+
+            mock_subprocess_run.return_value = MagicMock()
+
+            lang = ModelLang.ENGLISH
+            core = ModelCore.NEWS
+            size = ModelSize.SMALL
+
+            nlp = ModelSelector.select(lang, core, size)
+
+            mock_subprocess_run.assert_called_once_with(
+                ['python', '-m', 'spacy', 'download', 'en_core_news_sm'], check=True
+            )
+            assert mock_spacy_load.call_count == 2
+            assert isinstance(nlp, MagicMock)
+
+    def test_select_model_download_failure(self):
+        with patch('spacy.load', side_effect=OSError), patch(
+            'subprocess.run', side_effect=subprocess.CalledProcessError(1, 'cmd')
+        ) as mock_subprocess_run:
+            lang = ModelLang.ENGLISH
+            core = ModelCore.NEWS
+            size = ModelSize.SMALL
+
+            with pytest.raises(RuntimeError):
+                ModelSelector.select(lang, core, size)
+
+            mock_subprocess_run.assert_called_once_with(
+                ['python', '-m', 'spacy', 'download', 'en_core_news_sm'], check=True
+            )
+
+
+class TestSensitiveData:
+    @pytest.fixture
+    def sensitive_data_instance(self):
+        return SensitiveData()
+
+    @pytest.fixture
+    def mock_nlp(self, monkeypatch):
+        mock_nlp = MagicMock()
+        mock_doc = MagicMock()
+        mock_doc.ents = [
+            MagicMock(text='John Doe', label_='PER'),
+            MagicMock(text='New York', label_='LOC'),
+            MagicMock(text='Acme Corp', label_='ORG'),
+            MagicMock(text='Miscellaneous', label_='MISC'),
+            MagicMock(text='NonSensitive', label_='NON_SENSITIVE'),
+        ]
+        mock_nlp.return_value = mock_doc
+
+        monkeypatch.setattr(SensitiveData, 'set_model', lambda self, *args: mock_nlp)
+        return mock_nlp
+
+    @pytest.fixture
+    def mock_empty_nlp(self, monkeypatch):
+        mock_nlp = MagicMock()
+        mock_doc = MagicMock()
+        mock_doc.ents = []
+        mock_nlp.return_value = mock_doc
+
+        monkeypatch.setattr(SensitiveData, 'set_model', lambda self, *args: mock_nlp)
+        return mock_nlp
+
+    def test_identify_sensitive_data(self, sensitive_data_instance, mock_nlp):
+        content = (
+            'John Doe works at Acme Corp in New York. Miscellaneous information about something. NonSensitive data.'
+        )
+        expected_output = [('John Doe', 'PER'), ('New York', 'LOC'), ('Acme Corp', 'ORG'), ('Miscellaneous', 'MISC')]
+
+        result = sensitive_data_instance.identify_sensitive_data(
+            ModelLang.ENGLISH, ModelCore.NEWS, ModelSize.SMALL, content
+        )
+        assert result == expected_output
+
+    def test_identify_sensitive_data_empty(self, sensitive_data_instance, mock_empty_nlp):
+        # Test with empty content
+        content = ''
+        expected_output = []
+
+        result = sensitive_data_instance.identify_sensitive_data(
+            ModelLang.ENGLISH, ModelCore.NEWS, ModelSize.SMALL, content
+        )
+        assert result == expected_output
+
+    def test_identify_sensitive_data_no_entities(self, sensitive_data_instance, mock_nlp):
+        mock_nlp.return_value.ents = []  # No entities
+        content = 'This is a sentence with no sensitive data.'
+        expected_output = []
+
+        result = sensitive_data_instance.identify_sensitive_data(
+            ModelLang.ENGLISH, ModelCore.NEWS, ModelSize.SMALL, content
+        )
+        assert result == expected_output
+
+    def test_set_model(self):
+        model_lang = ModelLang.PORTUGUESE
+        model_core = ModelCore.NEWS
+        model_size = ModelSize.SMALL
+        expected_language = Language()
+
+        model_selector_mock = MagicMock(spec=ModelSelector)
+        model_selector_mock.select.return_value = expected_language
+
+        with patch('shadow_data.pii.spacy.ModelSelector', return_value=model_selector_mock):
+            sensitive_data = SensitiveData()
+
+            result = sensitive_data.set_model(model_lang, model_core, model_size)
+
+            model_selector_mock.select.assert_called_once_with(model_lang, model_core, model_size)
+            assert result == expected_language
diff --git a/tests/test_anonymization.py b/tests/test_anonymization.py
index 596b2aa..30bc43c 100644
--- a/tests/test_anonymization.py
+++ b/tests/test_anonymization.py
@@ -3,8 +3,8 @@
 
 def test_anonymize_single_term():
     original_content = "The user's name is João Silva."
-    original_term = "João Silva"
-    to_replace = "ANONYMOUS"
+    original_term = 'João Silva'
+    to_replace = 'ANONYMOUS'
 
     expected_output = "The user's name is ANONYMOUS."
 
@@ -12,19 +12,19 @@ def test_anonymize_single_term():
 
 
 def test_anonymize_multiple_occurrences():
-    original_content = "João Silva bought a car. João Silva sold a house."
-    original_term = "João Silva"
-    to_replace = "ANONYMOUS"
+    original_content = 'João Silva bought a car. João Silva sold a house.'
+    original_term = 'João Silva'
+    to_replace = 'ANONYMOUS'
 
-    expected_output = "ANONYMOUS bought a car. ANONYMOUS sold a house."
+    expected_output = 'ANONYMOUS bought a car. ANONYMOUS sold a house.'
 
     assert TextProcessor.replace_text(original_term, to_replace, original_content) == expected_output
 
 
 def test_anonymize_no_match():
     original_content = "The user's name is Carlos Pereira."
-    original_term = "João Silva"
-    to_replace = "ANONYMOUS"
+    original_term = 'João Silva'
+    to_replace = 'ANONYMOUS'
 
     expected_output = original_content
 
@@ -32,38 +32,38 @@ def test_anonymize_no_match():
 
 
 def test_anonymize_partial_match():
-    original_content = "João Silva bought a car. João sold a house."
-    original_term = "João Silva"
-    to_replace = "ANONYMOUS"
+    original_content = 'João Silva bought a car. João sold a house.'
+    original_term = 'João Silva'
+    to_replace = 'ANONYMOUS'
 
-    expected_output = "ANONYMOUS bought a car. João sold a house."
+    expected_output = 'ANONYMOUS bought a car. João sold a house.'
 
     assert TextProcessor.replace_text(original_term, to_replace, original_content) == expected_output
 
 
 def test_anonymize_single_ipv4():
-    text = "The IP is 192.168.1.100."
-    expected_output = "The IP is 192.X.X.X."
+    text = 'The IP is 192.168.1.100.'
+    expected_output = 'The IP is 192.X.X.X.'
 
     assert Ipv4Anonymization.anonymize_ipv4(text) == expected_output
 
 
 def test_anonymize_multiple_ipv4():
-    text = "The first IP is 192.168.1.100, and the second IP is 10.0.0.1."
-    expected_output = "The first IP is 192.X.X.X, and the second IP is 10.X.X.X."
+    text = 'The first IP is 192.168.1.100, and the second IP is 10.0.0.1.'
+    expected_output = 'The first IP is 192.X.X.X, and the second IP is 10.X.X.X.'
 
     assert Ipv4Anonymization.anonymize_ipv4(text) == expected_output
 
 
 def test_no_ipv4_found():
-    text = "There is no IP address here."
+    text = 'There is no IP address here.'
     expected_output = text
 
     assert Ipv4Anonymization.anonymize_ipv4(text) == expected_output
 
 
 def test_anonymize_partial_ipv4():
-    text = "The IP address is 192.168."
+    text = 'The IP address is 192.168.'
     expected_output = text
 
     assert Ipv4Anonymization.anonymize_ipv4(text) == expected_output
