E-Commerce Industry
Organizations must align their internal policies, procedures, and technical controls with multiple compliance frameworks (e.g., GDPR, ISO 27001, SOC 2, PCI-DSS). Manually mapping internal controls against these frameworks is time-consuming, error-prone, and inconsistent across teams. Compliance officers and auditors spend excessive effort identifying policy gaps and preparing for audits, leading to delayed certifications and regulatory risks.
Use Generative AI (LLMs) to automatically analyze and compare organizational policies, control documents, and audit evidence against regulatory frameworks or standards. The model identifies missing controls, outdated clauses, or inconsistencies, and generates structured gap reports with suggested remediation steps.
Upload internal compliance documents (PDF, DOCX, XLSX) and framework text (regulatory standards) to a data lake or document store.
Use OCR and NLP pipelines to extract and clean text from policy documents.
Convert control statements into embeddings using models like OpenAI text-embedding-3-large or Azure OpenAI embeddings.
Use OpenAI GPT-4 or Azure OpenAI with Retrieval-Augmented Generation (RAG) to generate summaries of mismatches and remediation recommendations.
Store processed documents and embeddings in a vector database (e.g., Pinecone, Weaviate, or Databricks Vector Search).
Export gap summaries to Power BI, Confluence, or GRC tools like ServiceNow or Archer.
You are a compliance audit assistant. Compare the internal 'Information Security Policy' with ISO 27001 Annex A controls. Identify which requirements are missing or weakly defined and suggest remediation steps.Reduces manual compliance mapping effort by up to 70%.
Improves detection of overlooked or partially implemented controls using semantic AI understanding.
Accelerates audit preparation and ensures traceable compliance documentation.
Minimizes regulatory exposure by identifying gaps early and automating remediation tracking.
import openai
import pandas as pd
policy_df = pd.read_csv('internal_controls.csv')
iso_df = pd.read_csv('iso27001_annexA.csv')
prompt = f'''You are a compliance auditor. Compare the following internal controls to ISO 27001 Annex A. Highlight missing or weak controls and provide remediation steps.
Internal Controls:
{policy_df.head(5).to_markdown()}
ISO Controls:
{iso_df.head(5).to_markdown()}'''
response = openai.ChatCompletion.create(
model='gpt-4-turbo',
messages=[{'role': 'system', 'content': prompt}]
)
print(response['choices'][0]['message']['content'])