Solution
Accenture deployed a production-grade AI platform on Azure AI Foundry that orchestrates responsible AI at enterprise scale. The system ingests enterprise knowledge and client data, leveraging Azure Machine Learning for custom model training and Azure AI Foundry Models for fine-tuning foundational models to specific domains. Azure AI Search enables retrieval-augmented generation for grounded, contextual responses, while Azure Functions and App Service manage application state and event-driven agent workflows. Safety is enforced through layered Azure AI Content Safety filters pre- and post-response, with continuous evaluation across dimensions like groundedness, coherence, and jailbreak resistance. Observability is provided by Azure Monitor and Application Insights, tracking every model call, user interaction, and agent decision for compliance and debugging across regulated industries.
Data flow
Enterprise-specific knowledge is ingested and indexed into Azure AI Search vectors. User queries flow through the application, which retrieves grounded context from search, processes through fine-tuned models via Azure Machine Learning, passes through Azure AI Content Safety filters, and returns compliant responses. Application state and agent memory are persisted in Azure Functions. All interactions, model calls, and decisions are logged to Azure Monitor for real-time observability and continuous improvement cycles.
Solution architecture
7 components · 4 layers - Compute
- Azure AI Search Enables retrieval-augmented generation to index enterprise knowledge and provide grounded, contextually relevant responses without hallucination.
- Azure Machine Learning Powers custom model training and domain-specific fine-tuning for specialized AI applications across multiple industry verticals.
- Orchestration
- Azure AI Foundry Unified platform for orchestrating agent workflows, evaluating outputs, and maintaining observability throughout the AI application lifecycle.
- Azure Functions & App Service Manage application state, agent memory, and event-driven orchestration with seamless interoperability to internal systems and third-party APIs.
- Governance
- Azure AI Content Safety Enforces multi-layer safety filtering to detect and remove personal data, offensive language, and policy violations from model responses.
- Azure Monitor & Application Insights Provides unified observability and traceability for all model interactions, agent decisions, and system behavior across distributed deployments.
- Uncategorized
- Microsoft AI Red Teaming Agent Proactively validates multi-agent workflows and detects model and application risk posture through simulation of adversarial scenarios before production.
- Azure AI Foundry Observability with Azure Monitor + Application Insights for full traceability
- Azure AI Foundry as unified SDK for safety, accuracy, and performance tracking
- Azure AI Search for RAG with indexed, vectorized enterprise knowledge
- Azure App Service for modular, event-driven agent workflows
- Azure Functions persist application state, session metadata, and agent memory
- Iterative AI red teaming simulations and A/B comparisons against golden datasets
- Microsoft AI Red Teaming Agent simulates adversarial prompts and detects model and application risk posture
- Two-layer cascading safety nets pre- and post-response using Azure AI Content Safety
Accenture delivered 17 use cases in just four months. That’s the power of having a unified, Azure-native foundation.
Accenture has already deployed 75+ use cases across industries, with 16 in production, reducing AI app build time by 50%.
Azure AI Foundry gives us a unified view across all our applications. Instead of stitching together a dozen tools, we had a single SDK to track safety, accuracy, and performance.
We were able to establish two layers of filtration. Even if one misses something, the second catches it. That’s peace of mind at scale.
