Blackbox Optimization
No Formula? No Problem.
Your Data Has Patterns. kint Finds Them.
Upload historical decisions and outcomes. kint trains a surrogate model that learns the relationship between inputs and outputs. Then optimizes using that learned model.
The Concept
What Is Blackbox Optimization?
You upload historical decisions and outcomes. kint trains a surrogate model that learns the relationship between inputs and outputs. The surrogate replaces the unknown formula. Then kint optimizes using that learned model to find the best decision for new situations.
When to Use
When Blackbox Is the Right Choice
You don't have a mathematical formula for the problem
You have historical data from past decisions and their outcomes
The relationships between inputs and outputs are complex or unknown
Harbor throughput optimization from operational logs
Process parameter tuning from production data
Demand-response modeling from sales history
Process
How It Works
Upload Data
CSV, database connection, API. Your historical decisions and their outcomes. kint accepts whatever format your team already uses.
Automatic Structure
kint identifies which columns are variables, which are constraints, and what the objective is. Your team reviews and adjusts.
Train Surrogate Model
XGBoost, Bayesian methods, or ensemble approaches. kint selects the best technique based on your data characteristics.
Optimize
kint optimizes using the learned model. The surrogate replaces the unknown formula. The result includes confidence scores.
Results
What Your Team Gets
Predictions for New Scenarios
What would happen if you changed this parameter? The surrogate model predicts the outcome without running a real experiment.
Confidence Scores
Every prediction comes with a confidence interval. High confidence means the model has seen similar data. Low confidence means caution.
Continuous Improvement
As more data arrives, the surrogate model gets better. Re-train with new outcomes. The predictions sharpen over time.
Comparison
Blackbox vs. Whitebox
| Whitebox | Blackbox | |
|---|---|---|
| Input | Mathematical model | Historical data |
| Formula needed | Yes | No |
| Result guarantee | Proven optimal | Best found |
| Improves over time | No (model is fixed) | Yes (more data = better) |
| Best for | Known structure | Unknown relationships |
Have a Formula Already?
If you can define your problem mathematically, whitebox optimization gives you a proven optimal answer.
Learn about Whitebox OptimizationSee It With Your Own Data
Bring a sample dataset. We'll train a surrogate model live and show you what kint finds. 30 minutes. No commitment.