Meet Your New AI Engineer.

Connect your data and describe your goal, or let your AI agents handle it for you. Genematon autonomously builds, trains, and deploys your custom ML and GenAI pipelines.

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Limited early access slots available.

How It Works

Three steps to production-ready ML & GenAI pipelines

agent-api-session
> POST /v1/agent/create-pipeline
[ok] Authenticated Agent ID: agt_9x8f2k
[ok] Goal parsed: "Predict customer churn"
[..] Generating pipeline architecture...
- Handling missing values in 'last_login_date'
- Engineering time-series features
- Training XGBoost and LightGBM ensembles
[..] Evaluating models...
[ok] Selected LightGBM (AUC-ROC: 0.942)
> POST /v1/agent/deploy
[ok] Pipeline active. API ready for agent consumption.

Genematon provides a full API that lets your AI agents autonomously create, deploy, and manage pipelines — no human in the loop required.

1

Connect Your Data

Connect data sources like databases, files, or data warehouses. Genematon handles the messy parts like data cleaning, validation, feature engineering, and prompt optimization.

2

Describe Your Goal

Tell Genematon what you want to achieve in plain English. It autonomously designs architectures, generates multiple solutions, evaluates them against your data, and selects the best performing model or prompt strategy.

3

Deploy to Production

Deploy your pipeline with monitoring, automatic retraining, and failover configured. No DevOps or ML team required.

Competition-Proven Technology

We used Genematon to build a supply chain forecasting pipeline for a Kaggle competition. It won first place.

Kaggle Competition Winner

If an autonomous AI engineer can beat hand-crafted solutions from human experts, imagine what it can do for your business.

Stop Waiting on AI Projects

Most ML and GenAI initiatives stall in the prototype phase. Genematon gets you to production while your competitors are still trying to hire an engineering team.

Get Early Access