Data and ML models.
Forecasts, recommendations and insights from your data. ML, DL and LSTM — for better decisions.
/ What we build
From data — to decisions.
Forecasting
Demand, inventory, sales.
LSTMRecommendations
Personalised offers.
E-COMMERCEAnomalies
Deviations spotted in time.
RISKClassification
Documents and requests — sorted.
NLPComputer vision
Image analysis and quality control.
COMPUTER VISIONData infrastructure
Pipelines and model architecture.
DATA ENGINEERING
/ Process
/ Consulting
First — the data.
We assess which questions your data can answer.
Book a consultationData audit
Quality, volume, potential.
ML opportunities
Where models will add the most value.
Model architecture
What to choose for your specific case.
/ Technologies
- Python
- PyTorch
- TensorFlow
- scikit-learn
- XGBoost
- LSTM
- Pandas
- Spark
- BigQuery
- Postgres
- MLflow
- Hugging Face
/ FAQ
Frequently asked questions.
How much data do we need?
It depends on the task. We start with what you have.
What is LSTM good for?
Forecasting: demand, prices, workloads.
Can you just consult?
Yes. A data audit is a separate service.
What will we see in the results?
Depending on the task, forecast values and their probabilities.
How much does it cost?
It depends on the task. We quote after a conversation.
/ Other services
/ Next step
Have data?
We have ideas.
Tell us about it — we’ll suggest a solution. Or let’s start with a consultation.