MLOps Platform Built to Scale.

Build ML.

JFrog ML (formerly Qwak) gives you all you need to deliver AI applications at speed, from idea to high-scale. Build, deploy, manage and monitor all your AI workflows, from GenAI and LLMs to classic ML, in a single platform.

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Chosen by the world’s best AI teams

Unified MLOps Platform

MLOps

LLMOps

Feature Store

MLOps

Train and Deploy Any Model

Build any model

Centralize model management from research to production, enabling team collaboration, CI/CD integration, and visibility into training parameters and metadata.

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Build AI and ML models with the qwak models registry

Easily train models

Train and fine-tune any model with one click on GPU or CPU machines, supporting all model types and enabling easy periodic retraining automation.

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Easily train and fine-tune any AI models with a single click with Qwak model training

Deploy models at scale

Deploy models to production at any scale with one click, serving them as live API endpoints, executing batch inference on large datasets or as streaming model connected to Kafka streams, with multi-version deployments.

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Deploy AI to production at any scale with Qwak model serving

Monitor models in real time

Monitor model performance, detect data anomalies, track input data distribution shifts, and integrate with tools like Slack and PagerDuty for real-time health and performance tracking.

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Monitor model performance and data anomalies in real time with Qwak model monitoring.

LLMOps

Develop LLM Applications

Manage prompts and track versions

Manage prompts with a single registry, allowing prompt creation and deployment in production, team collaboration, experimentation, version tracking, and a dynamic prompt playground.

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Manage prompts, track prompt versions, and seamlessly collaborate with your team with Qwak Prompt Management

Deploy optimized LLMs in one click

The Qwak LLM Model Library provides effortless deployment of optimized open-source models such as Llama 3, Mistral 7b, and more. Models can be deployed in just one click on your cloud or ours and automatically scale.

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LLM fine tuning on the Qwak LLM platform

Build complex workflows

Create and visualize complex LLM flows. Implement shadow prompts deployments to thoroughly test and refine them before rolling out your workflow into production.

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Easily organize and visualize complex LLM flows with Qwak workflows for LLM applications.

Trace LLM requests

Trace and inspect any workflow for LLM applications with ease. View all requests in one place, gain complete visibility, and debug your LLM workflow in seconds. Track prompt content, model inference calls, and latency.

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Easily trace any workflow for simple LLM debugging and Qwak LLM tracing

Monitor LLM applications

Monitoring LLMs in production for optimal performance and reliability. Track metrics like response time and identify issues quickly. Integrate with tools like Slack and PagerDuty.

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Monitor LLM pipelines and LLM applications with Qwak monitoring

Feature Store

Transform Your Data

Manage all features

The entire feature lifecycle managed in one feature store, allowing feature collaboration, ensuring consistency, and enhancing reliability in feature engineering and deployment.

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The entire feature lifecycle managed in one feature store the Qwak Feature Store

Ingest data from any source

Ingest data from warehouses and multiple sources, process and transform features, store them in a feature store, and create features and build data pipelines with custom transformations across various data sources.

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Store vectors at scale

Store embedding vectors at scale to supercharge your ML and AI applications by ingesting data from any source, converting it to embedding vectors, performing vector search, finding similarities for recommendation engines and RAG pipelines to enhance LLM applications.

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Store embedding vectors at scale to supercharge your ML and AI applications with the Qwak vector store

“JFrog ML streamlines AI development from prototype to production, freeing us from infrastructure concerns and maximizing our focus on business value.”

Edward Zhou

Software Engineer

Your entire AI/ML lifecycle in a single MLOps platform

Scale your AI/ML workflows with ease, eliminating the hassle of managing multiple tools and systems for your AI deployments.

Your entire AI/ML lifecycle in a single platform

Feature engineering & data pipelines

Remove the complexity of scalable feature engineering with the JFrog ML Feature Store & AI Platform in one. Gone are the days where you need high data loads to constantly update features and efficiently manage and scale data operations.

Collaborate with all stakeholders in one place

A single platform for ML engineers, data scientists, product managers, and AI practitioners to work on all AI projects in perfect sync.

Scalable model deployment

Deploy and fine-tune any model, including any embeddings models, open-source LLMs and more.

Feature Store

Unify your feature store and AI platform into one.

Consolidate your feature lifecycle efforts

Seamlessly use features as model inputs

Transform and persist your data in a single location

Manage and track all data applications & costs in one platform

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Unify your feature store and AI platform into one.

We help customers optimize AI & ML models in production

Edward Zhou

Software Engineer

“JFrog ML streamlines AI development from prototype to production, freeing us from infrastructure concerns and maximizing our focus on business value.”

Ryan Rollings

Principal Machine Learning Engineer

“We ditched our in-house platform for JFrog ML. I wish we had found them sooner.”

Asi Messica

VP Data Science

“The JFrog ML platform enabled us to deploy a complex recommendations solution within a remarkably short timeframe. JFrog ML is an exceptionally responsive partner, continually refining their solution.”

Idan Benaun

Director of ML and Data Science

“People ask me how I managed to deploy so many models while onboarding a new team within a year. My answer is: JFrog ML.”

Filip Gvardijan

Data Science Manager

“With JFrog ML, our AI team efficiently manages and deploys various models, both batch and real-time. The addition of an observability and Vector DB layer has been a game-changer, allowing us to confidently bring 10 models into production. JFrog ML's robust and streamlined approach has significantly enhanced our operational efficiency.”

Idan Schwartz

Head of Research

“Before JFrog ML, delivering a new AI model took weeks... Now the research team can work independently and deliver while keeping the engineering and product teams happy.”

Or Hiltch

VP Engineering

“Using JFrog ML allowed us to focus on creating value for customers rather than spending valuable time on our infrastructure setup.”

Jonathan Yaniv

Head of Data Science

“Our data science teams deliver end-to-end AI model services. Building infrastructure, however, is not our business focus, making JFrog ML ideal for our needs.”

Eyal Solnik

Head of Data

“With JFrog ML's intuitive AI Infra platform and AWS, we achieve operational efficiency and smarter personalized experiences. We get to make data-driven decisions impacting the customers and driving the company metrics.”

Elad Silvas

Data Science Manager

“With JFrog ML we were able to improve our AI delivery dramatically.”

Shaked Zychlinksi

Head of Recommendations Research

“From the get go, it was clear that JFrog ML understood our needs and requirements. The simplicity of the implementation was impressive.”

Elad Weiss

Data Science Team Lead

“We had the data and we solved the problem. JFrog ML allowed our data science teams to deliver the models into production with ease and efficiency.”

Amiram Shachar

VP & General Manager

“JFrog ML helped us make a paradigm shift to our data science operations. We now deliver new models quickly and efficiently and with much less friction along the process.”

See how our customers win with JFrog ML