Ditch your complex stack, gain streamlined end-to-end MLOps

Qwak streamlines the entire ML development lifecycle with a single platform. Easily build ML projects at any scale using a centralized platform that contains everything you need to build ML.

Start building models

The world’s best AI teams use Qwak

Use Qwak for model building, deployment, collaboration notebooks, feature store, and vector store for all your ML projects.

Qwak is an MLOps platform designed to simplify the entire ML lifecycle, making it significantly easier for Data Science and ML engineering teams to navigate. By integrating essential production-grade requirements, such as performance monitoring, autoscaling, and data monitoring right out of the box, Qwak offers a user-friendly solution that minimizes the need for external setup or third-party tools.

Use Cases

LLMOps

Deliver and streamline the lifecycle of large language models with a single platform.

Fraud Detection

Build and maintain fraud detection models seamlessly with a single platform for streamlined pipeline management.

Recommender Systems

Streamline recommender system development and maintenance with a unified platform for model lifecycle management.

Search & Ranking

Simplify search & ranking model lifecycle with a single platform for continuous development and maintenance.

See more use cases

One platform that allows you to focus on what matters

One platform

Model Registry

Manage models in one place for research and production

Model Training

Train models of any size with a single click

Model Serving

Deploy models to production at any scale in just one click

Model Monitoring

Monitor model performance and data anomalies

Feature Store

Easily manage all your features in one place

Vector Store

Store and ingest embedding vectors at any scale

Feature + Vector Pipeline

Transform data into features and vectors at any scale

Managed Notebooks

Experiment with managed Jupyter notebooks

Qwak integrates with all stages
of the model lifecycle

Explore Integrations

HuggingFace

Snowflake

Kafka

PostgreSQL

BigQuery

JFrog

CatBoost

GitHub

MySQL

OpsGenie

Keras

Your ML Projects Don't Have to be Expensive

Free

Best suited for dev environments

Start Free

Up to 100 QPU/month for a year

Unlimited model versions on Qwak model registry

Train and deploy on scalable resources

Managed Jupyter notebooks

Transform, store and manage features in the Feature store

Automatic inference and training pipelines

Monitor models and features

Model A/B testing and traffic splitting

Up to 1GB in-memory and 10GB storage

Chat support

Pay As You Go

$1.2/QPU

Best suited for productions environments

Get Started

Everything in Free, plus:

Unlimited QPU

Multiple environments

<2 hours SLA for critical cases

99.8% uptime guarantee

Multi A-Z installation (DR)

Enterprise

Custom

Best suited for enterprise environments

Everything in Pay As You Go, plus:

Volume discounts for pre-commitments

Self hosted hybrid deployments

SSO login

RBAC support

Dedicated support channel

<1 hour SLA for critical cases

<2 hours for important cases

Dedicated Qwak architect hours/month

2 annual on-site workshops

99.9% uptime guarantee

Private VPC installation

Storage

The Qwak platform contains two types of storage. Super fast in memory storage which is primarily used for online feature store, and warehouse storage, used for offline feature stores, model analytics, and monitoring.

In memory

$72

/ GB

Storage

$60

/ TB

Qwak optimizes ML Model Production

Asi Messica

VP Data Science, Lightricks

“From our very first interaction, it was clear that Qwak understood our needs and requirements. Their platform enabled us to deploy a complex recommendations solution within a remarkably short timeframe. Moreover, Qwak is an exceptionally responsive partner, continually refining their solution.”

Amit Segev

R&D Group Manager - Data & AI, ONE ZERO BANK

“Our AI and Machine Learning pipelines are fundamentally built on Qwak's comprehensive platform, which has been a game-changer in our journey from the initial ideation to the full-scale production of our banking chatbot 'Ella 2.0'. ”