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Modern Office

Case study: AI Assistant for Marketing

Summary​

A multinational manufacturing company sought to modernize how its marketing and sales teams accessed knowledge from its marketing playbook in order to ensure quick access to information and message consistency across diverse global markets.

 

The company wanted an intelligent system that could answer queries about branding, campaigns and product positioning instantly — reducing the need for manual document searches and ensuring consistent communication across markets.

 

The solution — an AI Marketing Assistant built and deployed on Azure AI Foundry — enabled natural-language access to thousands of pages of playbook content. It leveraged Retrieval-Augmented Generation (RAG), Azure AI Search, Azure OpenAI models, and secure enterprise integration, resulting in a scalable and compliant AI-Powered Knowledge Assistant.

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The challenge

The company maintained a detailed Marketing Playbook consisting of strategy documents, brand guidelines, campaign blueprints and sales enablement materials. This knowledge was fragmented across:

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  • SharePoint sites, PDF's and PowerPoints
     

  • Internal wikis and Microsoft Teams folders
     

  • Legacy intranet repositories
     

 Pain points included:

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  • Time-consuming searches through large, unstructured document sets.
     

  • Inconsistent understanding of marketing standards across regional teams.
     

  • Difficulty onboarding new employees quickly.
     

  • No centralized way to query information conversationally.
     

The challenge was to transform this static corpus into an interactive, intelligent system — while ensuring data privacy, enterprise security and scalability across geographies.

Image by Vitaly Gariev

The solution
A Marketing AI Assistant was designed using Azure AI Foundry as the central orchestration and governance hub. The solution architecture followed a modular, RAG-based design, ensuring that the assistant always provided factual, document-backed responses aligned with company policy.

    Solution workflow:

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  • Data Ingestion & Vectorization: The Marketing Playbooks (including Documents from SharePoint, white papers, competitor analysis and approved messaging guides) were securely ingested. 

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  • Azure AI Search was utilized to chunk the documents and create high-quality vector embeddings.

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  • RAG Pipeline Orchestration: A Python-based RAG pipeline, managed within an Azure AI Project instance on the Foundry, connects the LLM and the vector index.

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  • Secure Generation: When a user asks a question the pipeline executes:

 - Retrieval: Azure AI Search performs a Hybrid Search (combining keyword and vector similarity) to find the most relevant sections of the Marketing Playbook.

 - Augmentation: The retrieved, official content is inserted directly into the prompt as context for the LLM.

 - Generation: The Azure OpenAI Service (using GPT-4.0 Turbo) synthesizes the context into a concise, on-brand and direct answer.

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  • Conversational Layer & User Experience

 - The assistant was integrated into Microsoft Teams via the Azure Bot Framework.

 - A secondary web-based interface was hosted on Azure App Service, accessible through the corporate intranet.

 - Conversation history and feedback data are logged in Azure Cosmos DB for analytics and retraining.

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  • Governance, Security, and Monitoring

 - Authentication handled through Azure Active Directory (AAD) and Managed Identities for API calls.

 - Role-based access control (RBAC) ensures users only access content relevant to their department or region.

 - Azure Monitor, Application Insights and Log Analytics Workspace provide observability and performance metrics.

 - A private endpoint architecture was used — no data leaves the customer’s Azure environment, ensuring GDPR and ISO 27001 compliance.

Business People Applauding

Tech stack

   Infrastructure 

  • Cloud Platform: Microsoft Azure

  • Compute: Azure Virtual Machine 

  • Storage: Azure Blob Storage for document repository

  • Networking: Azure Virtual Network with NSG for security

    Core Platform

  • Workflow Automation: n8n 

  • Container Runtime: Docker for service isolation

   AI & Data Processing

  • LLM: OpenAI GPT-4 Turbo 

  • Vector Database: Azure AI Search

  • Azure Cognitive Services

  • Embeddings: OpenAI text-embedding-3-large model

   Monitoring & Analytics

  • Azure Monitor

  • Log Analytics

   Security

  • Azure AD

  • SSL/TLS

  • Managed Identities

Benefits​

The deployment of the Strategic Marketing Playbook Assistant yielded immediate and quantifiable improvements, accelerating market readiness and improving operational quality.

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         Key strategic outcomes​

  • 70% reduction in time spent locating information from the marketing playbook.

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  • Competitive Agility: Sales teams can now respond to RFPs and market inquiries with approved, nuanced and accurate positioning instantly, shortening the sales cycle and increasing win rates.

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  • Centralized Message Governance: By enforcing the RAG principle, the solution guarantees that all answers are sourced from the single, latest, approved Marketing Playbook, eliminating message drift across global teams.

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  • Reduced Risk: Content Safety guards eliminate the risk of the model inadvertently generating non-compliant or inappropriate content, protecting the brand's reputation

Meeting

Conclusion​

The deployment of the Strategic Marketing Playbook Assistant within Azure AI Foundry provided the client not just with a productivity tool, but with a strategic asset for knowledge management and brand governance. By standardizing on the Azure AI ecosystem, the organization achieved a scalable, secure, and highly accurate solution that directly addressed the growing complexity of their global marketing operation. This success underscores how a well-engineered RAG pipeline can transform static corporate documentation into an intelligent, dynamic, and competitive advantage.

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