New architecture integrates Copilot, Azure OpenAI, Claude, and Perplexity to transform Microsoft Power BI into an AI-driven enterprise decision platform.
HOUSTON, TX, UNITED STATES, March 13, 2026 /EINPresswire.com/ — EPC Group, a leading artificial intelligence (AI) and business intelligence consulting firm, today announced an expanded enterprise AI architecture for Microsoft Power BI that extends Microsoft Copilot with five additional AI intelligence layers. The new solution enables organizations to operationalize advanced analytics, predictive modeling, and AI-driven insights across their Microsoft Fabric and Power BI environments.
The architecture integrates Copilot for Power BI with Azure OpenAI, OpenAI, Claude, Perplexity, automated machine learning (AutoML), Microsoft Cognitive Services, native AI-powered visuals, and open-source AI frameworks including Meta Llama and Mistral. Together these technologies transform Power BI from a traditional reporting platform into an intelligent decision engine capable of delivering predictive analytics, automated insights, natural language exploration, retrieval-augmented generation (RAG), agentic AI workflows, and AI-generated narrative explanations for executive decision-making.
“At most organizations, Copilot is only the starting point,” said Errin O’Connor, Founder and Chief AI Architect of EPC Group, recognized as one of the Top 10 AI Architects in North America. “Over the past two years, I have personally led the development of this multi-layer AI architecture to expand Power BI beyond Copilot into a complete enterprise decision intelligence platform. By integrating Microsoft Fabric, Azure OpenAI, and leading large language model platforms such as OpenAI, Claude, Perplexity, and open-source AI, organizations can unlock conversational access to governed data while enabling predictive and agentic intelligence across their analytics environments.”
The EPC Group architecture introduces a structured six-layer AI framework designed to standardize AI capabilities across Power BI deployments while maintaining enterprise-grade governance, security, and compliance.
Layer 1 – Copilot for Power BI
The first layer leverages Microsoft Copilot for Power BI, allowing business users to interact with enterprise datasets through natural language queries. Copilot enables the rapid creation of reports, automated generation of DAX measures, semantic model exploration, and conversational analytics that make complex datasets accessible to non-technical users.
Layer 2 – Native AI Visuals
The second layer standardizes Microsoft’s native AI-powered visuals within Power BI. These include Key Influencers, Decomposition Tree, Smart Narrative, anomaly detection, and Q&A visuals. EPC Group deploys these capabilities through a governed pattern library that ensures consistent modeling practices, row-level security enforcement, and explainable AI across enterprise dashboards. These AI visuals enable organizations to automatically identify drivers behind business performance metrics, uncover patterns in operational data, and generate human-readable explanations of complex analytics.
Layer 3 – Automated Machine Learning in Fabric Dataflows
The third layer introduces automated machine learning (AutoML) capabilities within Microsoft Fabric and Power BI dataflows. Using AutoML, organizations can build predictive models for scenarios such as customer churn prediction, revenue forecasting, demand planning, and risk analysis without requiring dedicated data science teams. EPC Group delivers repeatable implementation blueprints that train predictive models within dataflows, score datasets automatically, and publish results directly into Power BI semantic models and executive dashboards. This architecture allows predictive analytics to become part of everyday business intelligence workflows rather than a separate data science initiative.
Layer 4 – Large Language Model and Agentic AI Integration
The fourth layer integrates large language models (LLMs) and agentic AI workflows into the Power BI analytics stack. Through secure API integrations, Azure Functions, and retrieval-augmented generation (RAG) architecture backed by vector search, EPC Group enables Power BI environments to connect with leading AI platforms including Azure OpenAI, OpenAI, Claude, Perplexity, and open-source models such as Meta Llama and Mistral. These integrations enable advanced natural language querying, contextual data exploration, semantic search across enterprise knowledge bases, and automated narrative generation that can explain trends, anomalies, and business drivers in plain language. EPC Group’s agentic AI layer allows AI models to autonomously retrieve, reason over, and act on enterprise data — surfacing insights proactively rather than waiting for users to ask.
Layer 5 – Microsoft Cognitive Services Enrichment
The fifth layer incorporates Microsoft Cognitive Services into enterprise data pipelines. These services enable text classification, sentiment analysis, language detection, entity extraction, and document intelligence to enrich structured and unstructured data before it enters Power BI datasets. For example, organizations can analyze customer feedback, support tickets, contracts, and survey responses using AI-driven text analytics. The enriched results can then be surfaced within dashboards as measurable business metrics, allowing leadership teams to quantify customer sentiment, operational risks, and market trends.
Layer 6 – Automated Insights and Forecasting
The sixth layer introduces automated insight generation and forecasting capabilities directly into executive dashboards. Using Power BI’s Quick Insights, built-in forecasting algorithms, anomaly detection models, and Copilot-generated narrative explanations, organizations can create dashboards that continuously surface emerging trends and risks. These capabilities enable business leaders to move from reactive reporting toward proactive decision-making. Executives can receive automated alerts when anomalies occur, view predictive forecasts for revenue or operational performance, and understand the underlying drivers behind those predictions.
Transforming Business Intelligence into Decision Intelligence
By combining these six layers under a unified responsible AI governance framework, EPC Group enables organizations to transform traditional dashboards into AI-powered decision intelligence platforms. Instead of simply viewing historical data, executives gain access to predictive insights, agentic AI workflows, automated explanations, and conversational analytics capabilities that dramatically accelerate decision-making. The architecture is designed to integrate seamlessly with Microsoft Fabric, Azure Data Services, enterprise data warehouses, and modern cloud analytics environments.
EPC Group delivers this architecture through its Power BI and Microsoft Fabric consulting services, including enterprise data modeling, AI integration, governance frameworks, dashboard architecture, and scalable deployment automation. The firm has completed more than 1,500 Power BI implementations and over 5,200 Microsoft platform deployments worldwide, helping organizations modernize analytics platforms across Microsoft 365, Azure, and Microsoft Fabric environments. With nearly three decades of Microsoft consulting experience, EPC Group combines deep technical expertise with enterprise AI strategy to help organizations deploy analytics platforms that are secure, scalable, and capable of supporting the next generation of AI-driven decision-making.
Organizations interested in extending Microsoft Copilot and Power BI with multi-model, agentic, and open-source AI solutions can learn more at www.epcgroup.net, schedule a strategy session with EPC Group’s AI and Power BI experts, or contact the firm directly at contact@epcgroup.net or (888) 381-9725.
Michelle Stevens
EPC Group
contact@epcgroup.net
Visit us on social media:
LinkedIn
Bluesky
Instagram
Facebook
YouTube
TikTok
X
Other
Power BI + AI Done Right: The $50 Million Integration Opportunity
Legal Disclaimer:
EIN Presswire provides this news content “as is” without warranty of any kind. We do not accept any responsibility or liability
for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this
article. If you have any complaints or copyright issues related to this article, kindly contact the author above.
