Problem framing
Define the business question, the target, and how success will be measured.
Custom ML Models
Machine learning models built for your data and goals.
Off-the-shelf models rarely fit real business data. Shaaneiol Tech designs, trains, and deploys custom machine learning models that solve your specific problem and keep improving.
- Classify
- Predict
- Cluster
- Recommend
Your data. Your problem. A model that fits.
What we deliver
Model development from raw data to production
A connected approach to turning your data into models that perform in the real world.
Data preparation
Clean, label, and shape your data so the model learns from reliable signals.
Model training
Train and compare algorithms to find the best fit for your problem.
Evaluation & testing
Test on unseen data and report results in terms the business understands.
Deployment
Release models behind simple APIs or into your existing systems.
Monitoring & retraining
Watch for drift and retrain so accuracy holds as your data changes.
Our process
From business question to deployed model
A clear delivery path, with priorities you can understand and progress you can follow.
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01
Frame
Turn the business question into a clear prediction task.
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02
Prepare
Collect, clean, and label the data the model needs.
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03
Train
Build and compare models, then tune the best one.
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04
Deploy
Release the model into your systems with monitoring.
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05
Retrain
Track drift and update the model over time.
Focus areas
Where custom models create value
Pick the tasks where learning from your own data beats fixed rules.
- Classification
- Regression
- Clustering
- Recommendation
- Anomaly detection
- Scoring
- Forecasting
- Feature engineering
Deliverables
Model assets your team can own
Trained model. Clear metrics. Ready to run.
Problem brief
The goal, target, and success metrics agreed in writing.
Prepared dataset
Cleaned data and features with documented sources.
Trained model
The selected model with its settings and version.
Evaluation report
Accuracy, errors, and limits in plain language.
Deployment package
An API or batch job ready for your systems.
Monitoring plan
How to track drift and when to retrain.
Why Shaaneiol Tech
Models that earn their place in production.
Combine sound data work with honest evaluation, so you know what a model can and cannot do before you rely on it.
Built on your data, not a template.
Start from your question and your records. Choose the simplest model that meets the target, and show clearly how well it performs.
Honest evaluation
Results measured on data the model has not seen.
Clean engineering
Reproducible code your team can maintain.
Data privacy
Access control and safe handling of sensitive data.
Ongoing care
Monitoring and retraining after launch.
Questions, answered clearly.
Can’t find what you need? Let’s have a quick, no-pressure conversation.
How much does a custom ML model cost?
Cost depends on data readiness, problem complexity, and deployment needs. We start with a short feasibility study to give a clear estimate.
How much data do we need?
It depends on the task. Some problems work with a few thousand records, others need more. We assess this before committing to a build.
How long does a model take to build?
A first working model often takes a few weeks. Production deployment and monitoring add time depending on your systems.
How do we know the model is accurate?
We test on data the model has not seen and share the results, including where it fails, so you can decide with full information.
Hire Our Dedicated ML Engineers
Turn your data into models that predict, classify, and recommend, built by engineers who ship to production.