Defined an AI adoption roadmap across 500+ business processes, designing a hybrid RAG architecture with validated ROI for enterprise handover.
Delivered strategic AI advisory from POC to a validated, scalable architecture. MS Copilot serves as the primary user interface—eliminating custom UI costs while targeting high adoption. The hybrid RAG and automation design address accuracy, freshness, and operability at enterprise scale; ROI framing and handover positioned internal owners to execute.
The Challenge
An isolated AI Proof of Concept had to become a production-ready direction for 500+ processes. The mission was to run the full consulting arc—use-case identification, prioritization, strategic conceptualization, and ROI validation—so the program could scale beyond experiments without betting on costly custom UI.
The Solution
Evaluated and prioritized high-impact AI use cases across 500+ departments, shifting the narrative from “experimental” AI to business-critical automation. Designed the technical pivot from a fragile “Master Excel” to a Hybrid RAG architecture: semantic vector search combined with a structured metadata/taxonomy layer so logic stays accurate (e.g. process successors and responsibilities). Conceptualized an automated ETL pipeline via Power Automate to ingest and vectorize new PDFs weekly, keeping the knowledge hub current without manual intervention. Calculated strategic ROI (development vs. schooling hours) and handed over a final blueprint to internal teams for implementation.
Outcomes
Prioritized AI use cases across 500+ departments toward business-critical automation.
Hybrid RAG: vectors plus metadata/taxonomy for dependable process logic.
Weekly PDF ingestion and vectorization via Power Automate—minimal manual upkeep.
ROI validated (development vs. schooling); blueprint delivered for internal build-out.
Copilot-first interface: scalable adoption without a custom UI program.
