By Smart Associates | Powered by IBM Netezza with INZA Analytics

From Raw Data to Production ML in Record Time

FeatureFactory is a complete feature engineering, model management, and data governance platform from Smart Associates. Profile data, build features, train models, and monitor drift: all from a single, unified interface.

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Dashboard

Built On Trusted Technology

Capabilities

Everything You Need for ML at Scale

From data profiling through to production deployment, FeatureFactory covers the entire machine learning lifecycle with tools designed for enterprise data teams.

Data Quality Profiling

Automatically profile your tables to understand completeness, distribution, and quality. Identify issues before they propagate through your pipeline.

Feature Engineering

Define, group, and materialize features using SQL expressions executed natively inside Netezza. Organise features into reusable sets tied to entity types.

AutoML Model Training

Train classification, regression, clustering, and time series models using INZA algorithms. A guided wizard handles algorithm selection, hyperparameters, and evaluation.

Governance & Compliance

Track data lineage, enforce policies, manage master data, and maintain audit trails. Built-in compliance automation helps meet regulatory requirements.

Drift Detection & Monitoring

Continuously monitor data and model drift with configurable alert thresholds. Catch distribution shifts early, before they degrade model performance.

Spatial & Time Series Analytics

Run geospatial queries with ESRI integration and time series forecasting natively inside the warehouse, bringing advanced analytics closer to your data.

Workflow

Six Steps from Data to Deployment

FeatureFactory provides a guided path through the entire ML lifecycle, so your team can focus on insight rather than infrastructure.

01

Profile Your Data

Connect to Netezza tables and run automated profiling to assess completeness, distributions, and anomalies.

02

Create Features

Define feature expressions in SQL. Each feature is versioned, documented, and tied to source tables for full lineage.

03

Build Feature Sets

Group related features by entity type (customer, transaction, product) into reusable, shareable sets.

04

Materialize & Schedule

Compute feature values on demand or on a schedule. All processing happens inside the data warehouse for maximum performance.

05

Train Models

Use the AutoML wizard to select algorithms, configure parameters, and train models using INZA's in-database analytics.

06

Deploy & Monitor

Push models to production, monitor for drift, and track effectiveness over time with built-in alerting.

See It in Action

A Platform Built for Your Team

From guided onboarding to business impact tracking, FeatureFactory gives everyone a clear path from raw data to deployed models.

FeatureFactory — Getting Started

Why FeatureFactory

Compute Where Your Data Lives

FeatureFactory pushes computation into IBM Netezza, eliminating data movement and leveraging the massively parallel processing engine you already own. Features, models, and analytics all run inside the warehouse.

  • In-database ML with INZA: no data extraction required
  • Role-based access control with full audit trail
  • RESTful API for integration with existing pipelines
  • Geospatial and time series analytics built in

Ready to Accelerate Your ML Pipeline?

See how FeatureFactory can help your team move from raw data to production models faster, with full governance and monitoring built in.

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Coming Soon: Open Source

Join the Waitlist

We're porting FeatureFactory to PostgreSQL, Greenplum, and beyond, and open-sourcing everything. Be the first to know when it's available, and help shape the product.

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PostgreSQL + MADlib
Greenplum & Cloudberry
100% Open Source
Commercial Support Available