Build Powerful Predictive AI Solutions — Faster — with FeatureByte¶

FeatureByte transforms how teams discover, build, and deploy machine-learning features and models.

By automating feature generation across complex multi-table relational datasets, FeatureByte accelerates the path from business problem to production-ready models, reducing the need for manual exploration, SQL development, and repetitive iteration.

Designed for data scientists, ML engineers, and business stakeholders, FeatureByte can be adopted end-to-end or used solely for experimentation while integrating with your existing production pipelines.

🔄 Before FeatureByte vs. With FeatureByte¶

Before FeatureByte	With FeatureByte
Manual feature brainstorming and SQL prototyping	Automated discovery and evaluation of feature candidates directly from relational data
Long iteration cycles to test new ideas	Rapid evaluation and refinement of features and models
Difficult to reuse features across teams	Centralized, reusable, versioned feature assets
Separate tools for feature engineering, modeling, and deployment	Centralized workflows across ideation, training, deployment, and governance
High engineering effort to productionize features	Streamlined deployment of governed feature pipelines and models
Limited visibility into lineage, documentation, and approvals	Built-in lineage tracking, documentation, and approval workflows
Inconsistent processes across teams	Standardized, repeatable ML workflows

✨ Why FeatureByte?¶

Native Data Platform Execution

Computation happens directly in your environment (Databricks, Snowflake, BigQuery, Spark) to minimize data movement.
Automation with Configurability

Feature and model suggestions are automatically generated, and teams can refine, validate, and configure results.
End-to-End Workflow

A unified platform covering feature discovery, model development, model comparison, refitting, and deployment.
Unified Governance

All features, models, and evaluation artifacts are centrally documented and governed with lineage and RBAC.
Flexible Deployment Options

Deploy features and models for batch or real-time serving. SQL export for custom pipelines is coming soon.

👥 Who Is FeatureByte For?¶

FeatureByte supports the full spectrum of predictive-modeling teams:

Data Scientists: Rapidly generate and evaluate feature candidates and models.
ML Engineers: Ship governed, scalable pipelines.
Analytics Leaders: Standardize workflows and accelerate ML delivery.
Business & Analytics Teams: Leverage automation without heavy engineering effort.

⚡ Streamlined Machine Learning Workflow¶

FeatureByte provides capabilities across each stage of the ML lifecycle—from feature discovery to production deployment.

1. Discover Features¶

Generate a wide range of features tailored to your use case, including point-in-time attributes, event-based aggregations (frequency, recency, timing), latest-event attributes, statistical summaries, diversity and stability metrics, similarity scores, and more.

Instead of manually writing SQL or hand-crafting features, FeatureByte provides three ideation modes:

Autopilot Mode: Automatically generates feature sets and model candidates.
Copilot Mode: Interactive, guided refinement.
Manual Mode: Full customization via the Python SDK.

Powerful Feature

2. Train & Evaluate Models¶

With features ready, FeatureByte supports model training, evaluation, and Feature List Simplification to reduce complexity without sacrificing performance.

Model Evaluation