Data Intelligence product
Keep models current as data arrives
Without a retraining pipeline
Ship models that keep learning from new live data, so predictions stay current without a retraining pipeline.
Start with a CSV or a database. No data science team required.
See Loops in Action
Watch how adaptive machine learning loops continuously learn and improve with every interaction
Adaptive Learning Flow
Watch your loop learn in real-time. Each prediction feeds back into training, creating a continuous improvement cycle.
Performance Metrics
Improving with each training cycle
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Each prediction includes feature contributions for explainability
Visual representation of the adaptive learning cycle
Continuous Improvement
Your loops automatically learn from every prediction. Feed new data back into the system and watch your models improve in real-time without manual retraining.
Real-time Training
Train your models with new data as it comes in
Automatic Updates
Models update automatically with new training data
Performance Tracking
Monitor how your loops improve over time
Explainable Predictions
Every prediction includes feature contributions showing which factors impact the result
Simple API Integration
Integrate loops into your applications with a simple REST API. Train and predict with just a few lines of code.
import requests
url = 'https://loop.heimdallapp.org/predict/'
headers = {
'X-api-key': 'YOUR_API_KEY',
'x-loop-id': 'YOUR_LOOP_ID'
}
response = requests.post(
url,
headers=headers,
json={'data': ...}
)Why Choose Loop?
Build adaptive machine learning solutions that improve automatically
Use cases
Loop use cases on Heimdall
Adaptive models that learn from live interactions — personalized feeds, recommendations, and ranking.
See warehouse workflows that feed these models on all Heimdall use cases.
Ship a model that keeps learning
Start from gold data, deploy an API, and let Loop update as new live samples arrive — so you are not retraining from scratch every week.