Skyulf

Own Your

ML Pipeline Locally.

The privacy-first MLOps workspace. Ingest data, engineer features visually, and train models without your data ever leaving your infrastructure.

Focus on the model, not the infrastructure.

Built for teams who want to focus on models, not glue code.

Visual Canvas

Drag, drop, and connect nodes to clean data and engineer features. No more spaghetti code in notebooks.

Background Training

Run heavy training jobs in the background. Powered by Polars for high-speed processing and Celery for robust task management.

One-Click Deploy

Go from experiment to production instantly. Serve predictions via a built-in REST API.

DATA INGESTION

Load your data.

Keep it on your machine.

Import CSV, Parquet, or SQL datasets directly. Powered by Polars, Skyulf auto-detects column types and caches everything for fast, repeatable experiments.

• ** Smart column type detection
• ** Built-in dataset caching
• ** No data leaves your network

EXPLORATORY DATA ANALYSIS

Understand your data.

Before you train.

Automated profiling, outlier detection, and causal discovery. Spot data quality issues instantly with our high-performance Polars-based engine.

• Decision Trees: Extract human-readable rules (e.g., "IF Age > 30...") to find key segments.
• Causal Discovery: Discover hidden cause-effect relationships using the PC Algorithm.
• Decomposition Trees: Interactively drill down into metrics across multiple dimensions.
• Interactive Plots: 3D PCA, Time Series decomposition, and Geospatial maps.

FEATURE ENGINEERING

Stop writing boilerplate.

Start designing pipelines.

The Feature Canvas lets you visualize your data transformations. Handle missing values, encode categories, scale features, and more—all with drag-and-drop nodes.

• ** 25+ Built-in processing nodes
• ** Real-time schema validation
• ** Reproducible pipeline exports

EXPERIMENT TRACKING

Compare runs.

Pick the winner.

Don’t guess which model is better. Track every hyperparameter, metric, and artifact. Visualize performance with interactive charts.

ROC

Curve Analysis

F1

Score Tracking

Acc

Model Accuracy

MAE

Error Metrics

DEPLOYMENT

Test your models

instantly.

Once you’re happy with a model, deploy it to a local inference endpoint. Verify predictions immediately with the built-in JSON editor before moving to production.

LOCAL INFERENCE

Validate models

before production.

Spin up a local API endpoint to test your model against real data. Debug inputs and outputs in real-time without deploying to a remote environment.

• ** Instant local API endpoints
• ** Interactive JSON request builder
• ** Rapid debugging cycle

MONITORING

Detect Drift.

Maintain Performance.

Continuous monitoring of your deployed models. Detect data drift, concept drift, and prediction anomalies in real-time to ensure model reliability.

• Drift Detection: Automatically compare production data against training baselines.
• Feature Analysis: Visualize distributions to pinpoint exactly which features are drifting.
• Automated Reports: Generate comprehensive HTML reports for stakeholders.

Who is this for?

Teams working with sensitive data who can’t upload to cloud services.

Healthcare & Research

Train models on patient data or research datasets that can’t leave your infrastructure due to GDPR or institutional policies.

• HIPAA and GDPR friendly workflows
• 100% on-premise processing

Government & Public Sector

Municipalities and public institutions working with citizen data that must stay on-premises for privacy and compliance.

• GDPR-compliant processing
• Full audit trails

SMEs & Startups

Small teams who need ML tooling but want to avoid expensive SaaS subscriptions and keep data under their own control.

• Zero-config SQLite start
• No per-user fees

Frequently Asked Questions

Everything you need to know about the platform and how it works.

Product tour

See Skyulf in action

From ingestion to deployment, Skyulf keeps your experiments reproducible and private. Here’s a snapshot of how a local-first team moves from raw data to a deployed model.

1

Load your data

Point to CSV, Parquet, or SQL sources. Schema gets detected automatically.

2

Build your pipeline

Drag nodes around the canvas to wire up transforms. Preview stats at each step.

3

Train & Deploy

Launch training runs in the background. Deploy the best model to a local API.

Powered by modern open source

Ready to build?

Join the local-first MLOps revolution. Open source and free forever for local use.

Launch Skyulf