Declarative ML: High Performance, Low Code

Finally, an alternative to AutoML.

State-of-the-art machine learning for engineers and data practitioners as easy as writing a SQL query.

From the creators of Ludwigand Horovod

Built by AI leaders from Uber, Google, Apple and Amazon. Developed and deployed with the world’s leading organizations.

What is Declarative Machine Learning?

Declarative machine learning systems provide the best of flexibility and simplicity to enable the fastest-way to operationalize state-of-the-art models. Users focus on specifying the “what”, and the system figures out the “how”.


Unlock cutting-edge deep learning on your dataset in just six lines.


Start with smart defaults, but iterate on parameters as much as you’d like down to the level of code.


Our team pioneered declarative machine learning systems in industry, with Ludwig at Uber and Overton at Apple.

How it works

Connect your data with a few clicks

Choose from our menu of prebuilt data connectors that support your databases, data warehouses, lakehouses, and object storage.

Unstructured data analytics

Automatically train models on top of Ludwig

Train state-of-the-art deep learning models without the pain of managing infrastructure.

Unstructured data analytics

Operationalize models, in a familiar way

Access models via REST, Python, or PQL - our slight extension of SQL that puts machine learning in the language closest to data.

Unstructured data analytics

Use Cases

Predibase works across supervised machine learning use cases such as:

Unstructured data analytics

Unstructured data analytics

Write SQL-like analytical queries over text, images, video, audio in addition to tabular data.

Predictive Lead Scoring

Predictive Lead Scoring

Predict the value of a lead and likelihood of conversion based on your historical data.

Customer Service Automation

Customer Service Automation

Classify incoming messages and predict responses to automate

Churn Prediction

Churn Prediction

Predict customer churn before it happens to increase retention

Anomaly & Fraud Detection

Anomaly & Fraud Detection

Detect anomalies or fraud in your data based on previously flagged results

Demand Forecasting

Demand Forecasting

Forecast future demand based on historical trends in your data.

Recommendation Systems

Recommendation Systems

Target recommendations based on previous user behavior to improve product engagement.

Many more

Many more

Predibase can support your machine learning use case, no matter how complex. Contact us to learn more about how we can help you with AI today.

Why Users Love Us:

State-of-the-art machine learning in your hands

Easily leverage powerful models such as BERT and GPT in production.

Glass Box, not Black Box

Automated Machine Learning that strikes the balance of flexibility and control, all in a declarative fashion.

Fits into existing workflows

Whether it’s PQL, Python, or REST, data users can choose what interface works for them.

ML Infrastructure, simplified.

Effortlessly scale training and deployment of ML without the headache.

Many more

Why Organizations Love Us:

ML in days, not months

With a declarative approach, finally train and deploy models as quickly as you want.

Democratizes access to machine learning

Equip your broader data organization to effectively use machine learning.

Unlock your company’s potential

Go from data to deployment like never before. The possibilities are endless.

Many more

Proven Open Source Technology


Ludwig is a deep learning toolbox to declaratively develop, train, fine-tune, test and deploy state-of-the-art models. Ludwig puts deep learning in the hands of analysts, engineers and data scientists without requiring low-level ML code.


Horovod is a distributed deep learning framework that scales PyTorch and TensorFlow training to hundreds of machines. It supports Tensorflow, Keras, Pytorch, Apache MXNet and has been used to productionize deep learning models across industries

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Integrates with

Predibase is built for the modern data stack, allowing data practioners to easily connect data wherever it lives.

We are hiring ML Engineers, Data Scientists, DevOps, and Systems Engineers