AI Digital Transformation Analysis Agent

How Cassidy automates using AI

Step 1: Trigger on document upload or scheduled sync

The Workflow activates when new transformation documents are added to connected sources—SharePoint, Google Drive, Confluence, or Box—or runs on a scheduled cadence to capture the latest versions across the client's document corpus.

Step 2: Ingest and normalize the document corpus

Cassidy applies OCR and layout-aware parsing to PDFs, PowerPoints, and scans, then normalizes metadata (owner, date, function, sensitivity) and de-duplicates near-identical versions to create a clean, searchable Knowledge Base.

Step 3: Map content to capability taxonomy

Using the Knowledge Base and domain-grounded prompts, Cassidy classifies extracted content against a capability model—linking processes, systems, teams, and risks to canonical taxonomy terms for consistent analysis across engagements.

Step 4: Score maturity and surface gaps

Cassidy evaluates document evidence against maturity dimensions (strategy, operating model, data governance, talent, Responsible AI) and generates a scored baseline with heatmaps, gap registers, and direct links to supporting source material.

Step 5: Identify and prioritize use cases

The Workflow mines pain points and process gaps to surface AI and automation opportunities, then scores each use case by value, effort, and dependencies—separating quick wins from foundational enablers and strategic bets.

Step 6: Generate deliverables with Human-in-the-Loop review

Cassidy drafts the executive readout, maturity scorecard, use-case cards, and sequenced roadmap. Consultants review and refine outputs before final delivery, ensuring every recommendation is defensible and client-ready.