Manufacturing data lives in your ERP, plant floor, and logistics systems — but decisions happen on the floor, in the moment. See how Sparkflow's AI-powered Natural Language Query lets manufacturing teams ask questions in plain English and get instant, accurate answers grounded in their real data — no SQL, no waiting on IT, no exporting to Excel.

Time Stamps

• 0:00 Intro: The Manufacturing Data Problem

• 0:56 Why Traditional Reporting Falls Behind

• 1:16 What Is Sparkflow Natural Language Query?

• 1:31 NLQ vs. Search Bars & Generic Chatbots

• 2:07 Manufacturing's Real-Time Data Challenge

• 2:51 Live Demo Begins

• 3:17 Demo: Total 2025 Revenue Query

• 3:45 Demo: Revenue by Customer

• 5:13 How Sparkflow Anticipates Your Next Question

• 6:08 Demo: Revenue by Product Code

• 7:43 Demo: Drilling Into a Single Category

• 8:15 Speed vs. Traditional Reporting

• 8:58 Guardrails: What Happens When Data Isn't Available

• 9:49 Data Security & Zero Data Retention

• 10:22 Implementation Timeline

• 11:11 Handling Multiple Data Sources

• 12:22 Team Training Requirements

• 13:21 Closing: Getting Started

What You'll Learn

• Ask questions in plain English and get answers grounded in your actual ERP data

• Watch live queries: total revenue, sales by customer, sales by product code, category drill-downs

• See the guardrails that stop the AI from guessing when data isn't available

• Understand how data security and zero data retention work

• Get a realistic implementation timeline and team training requirements