🌤️ The Story Begins: A Company Drowning in Uncertainty

A factory manager once said:

“I’m not afraid of problems. I’m afraid of not knowing what will happen next.”

She faced unpredictable inventory, sudden machine breakdowns, hidden defects, customer drop-offs, and constant firefighting.

She wanted certainty — so she came to us.

🔮 Simplico’s Role in the Story

We build AI prediction systems that turn uncertainty into clarity.
Systems that help businesses see problems before they happen and act with confidence.

🌱 Before Prediction → After Prediction

❌ Before

Guessing, reacting late, and firefighting every week.

✔️ After

Predicting, acting early, and staying in control.

🚀 Our Services — Real AI That Solves Real Problems (With User Stories)

Below are 5 prediction systems — each with a real scenario showing how a business can use it.

1. Demand & Sales Prediction System

📘 User Story

Nok, a production planner at a beverage factory, faces a recurring nightmare:
Every long weekend, sales spike without warning.
Her team always ends up working overtime or shutting down bottling because they ran out of bottles.

After installing our prediction system:

It forecasts next week’s sales volume
Suggests how many bottles to order
Predicts which SKUs will spike
Alerts her when demand will exceed capacity

Now Nok prepares confidently — no more emergency purchases.

✦ What the System Does

Forecast sales
Balance inventory
Create auto-reorder triggers
Predict staff requirements

2. Predictive Maintenance System

📘 User Story

Somchai, a maintenance supervisor at a machining factory, was tired of breakdowns that happened “out of nowhere.”
Scheduled maintenance didn’t match real machine health.

After using our predictive maintenance engine:

The system detected vibration anomalies
Predicted a spindle failure 3 days before it happened
Automatically sent him a maintenance alert
Prevented a week of downtime

Management saved hundreds of thousands — all from one prediction.

✦ What the System Does

Predict equipment failure
Schedule maintenance automatically
Reduce downtime
Increase machine lifespan

3. Image Classification & Quality Inspection

📘 User Story

Ann, a QC supervisor at an electronics factory, manually inspected thousands of parts each day.
Some defects were too small or inconsistent for the human eye.

She installed our image-based prediction system:

AI detected micro-cracks instantly
Marked defects with bounding boxes
Flagged high-risk items
Generated daily QC reports
QC speed increased by 300%

Her team now focuses on decision-making, not staring at defects.

✦ What the System Does

Detect visual defects
Classify authenticity (brand inspection)
Automate image-based QC
Highlight high-risk items

4. Customer Behavior Prediction

📘 User Story

Jane, a retail marketing manager, didn’t know why customers suddenly stopped buying certain products.
Promotions were hit-and-miss.

After installing our customer prediction engine:

It identified customers likely to churn
Predicted who is ready to buy again
Suggested promotion strategies
Auto-generated customer segments

Instead of guessing, Jane sends the right message to the right customer at the right moment.

✦ What the System Does

Predict churn
Predict purchase probability
Recommend next steps
Segment customers automatically

5. AI Workflow Automation (Prediction → Action)

📘 User Story

Krit, operations lead at a warehouse, used to manually check stock levels and generate purchase orders.

After adopting our automation pipeline:

AI forecasted low stock
Auto created POs
Sent alerts to suppliers
Synced with ERP system
Reduced stockouts by 90%

His warehouse now runs without constant human monitoring.

✦ What the System Does

Convert predictions into actions
Auto-generate orders
Auto-stop machines or lines
Auto-notify staff
Auto-generate reports

🧠 Our Development Philosophy

A prediction is valuable only when it improves a real decision.

📊 Mermaid Diagram — Prediction System Architecture

flowchart TD
    A["Business Problem"] --> B["Identify Key Decisions"]
    B --> C["Define Required Predictions"]
    C --> D["Collect & Prepare Data"]
    D --> E["Train Prediction Model"]
    E --> F["Evaluate & Validate Accuracy"]
    F --> G["Integrate Model into Workflow"]
    G --> H["Automated or Assisted Actions"]
    H --> I["Human Oversight & Feedback"]
    I --> J["Continuous Improvement Loop"]