Process Discovery Before AI Automation
How to map real work, exceptions, ownership, and evidence before deciding what AI should automate.
AI
Rules, RPA, ML, LLMs, and Agents: The Decision Ladder
A practical decision ladder for choosing between rules, RPA, traditional machine learning, LLM workflows, and agent-like systems.
AI for Voice of Customer, Objection Mining, and Messaging Insights
How to use AI to mine customer language, objections, and messaging patterns from real interactions without mistaking a few anecdotes for market truth.
AI-Powered Email Sorting
How to use AI to classify, prioritize, and route inbound email without turning your inbox into an uncontrolled black box.
Build a Simple AI Classification Pipeline
How to design a lightweight classification pipeline with a clear schema, confidence thresholds, review paths, and a realistic refresh cycle.
Document Auto-Summary Playground
What this demo proves, what it does not prove, how to evaluate it responsibly, and what would be required to turn it into a production summarization workflow.
When Not to Send Data to a Public LLM
How to decide when a business workflow should avoid public LLM endpoints, based on data sensitivity, contractual exposure, and safer design alternatives.
Where AI Helps and Fails in Accounting
A realistic view of where AI is useful in accounting work and where human controls, policy interpretation, and exactness still dominate.
The AI Stack in Plain English
A plain-English guide to the main layers of a modern AI system, from models and prompts to retrieval, tools, guardrails, and review.
AI for Ticket Triage and Case Routing
How to use AI to classify incoming cases, assign ownership, protect service levels, and escalate the right issues without losing operational control.