- 25 GB Base Consumption
- Community Support
- Universal Binary Repository
- Release Lifecycle Management
- Unlimited Docker Hub Pulls
- Complete Container Registry
- Cloud-native Managed Platform
Qwak
1
Qwak is an AI-powered platform that streamlines the process of data preparation, model development, and deployment, making machine learning accessible for users.
Large Language Models (LLMs)
Chord AI
AI Facebook
AI Log Management
#AI agent
#machine learning automation
#Data Preparation Tools
#model deployment
#User-Friendly ML
#feature engineering
#Performance Testing
#Collaboration in AI
#rapid deployment
#no-code machine learning
#data scientist tools
#analytics software
#Business intelligence
#integration capabilities
#Efficient ML Workflows
#ML Model Optimization
#AI for Analysts
#data processing solutions
#Simple ML Solutions
...
Promote this Tool
Update this Tool
Qwak is an AI-powered platform that streamlines the process of data preparation, model development, and deployment, making machine learning accessible for users.
Large Language Models (LLMs)
Chord AI
AI Facebook
AI Log Management
#AI agent
#machine learning automation
#Data Preparation Tools
#model deployment
#User-Friendly ML
#feature engineering
#Performance Testing
#Collaboration in AI
#rapid deployment
#no-code machine learning
#data scientist tools
#analytics software
#Business intelligence
#integration capabilities
#Efficient ML Workflows
#ML Model Optimization
#AI for Analysts
#data processing solutions
#Simple ML Solutions
...
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What is Qwak?
Qwak is an innovative AI Agent designed to simplify machine learning workflows. It automates key tasks such as data preparation, feature engineering, model selection, and deployment. By leveraging cutting-edge algorithms and a user-friendly interface, Qwak empowers users to build, evaluate, and optimize machine learning models without requiring extensive coding skills. This platform is ideal for data scientists, analysts, and businesses looking to harness AI technology quickly and effectively.
Who will use Qwak?
- Data Scientists
- Machine Learning Engineers
- Business Analysts
- Developers
- Researchers
How to use the Qwak?
- Step1: Sign up for a Qwak account.
- Step2: Upload your dataset.
- Step3: Use the platform's tools to prepare and clean your data.
- Step4: Choose the appropriate model from the available options.
- Step5: Train the model and evaluate its performance.
- Step6: Deploy the model for real-time predictions.
Platform
- web
- mac
- windows
- ios
- android
Qwak's Core Features & Benefits
The Core Features
- Data Preparation
- Model Creation
- Automated Deployments
- Performance Evaluation
- Collaboration Tools
The Benefits
- Increased Efficiency
- User-Friendly Interface
- Less Coding Required
- Faster Time-to-Deployment
- Integration with Other Tools
Qwak's Main Use Cases & Applications
- Predictive Analytics
- Customer Segmentation
- Sales Forecasting
- Fraud Detection
- Image Classification
Qwak's Pros & Cons
The Pros
Comprehensive all-in-one platform covering MLOps, LLMOps, and Feature Store.
Supports collaboration across multiple roles involved in AI projects.
Easy one-click training and deployment on both GPU and CPU.
Real-time model monitoring with anomaly detection and integrations for alerts.
Supports both batch and streaming model serving for flexible deployment.
Optimized deployment for popular open-source LLM models like Llama 3 and Mistral 7b.
Feature Store integrates data lifecycle management and vector store for embeddings.
The Cons
No explicit mention of mobile or desktop applications.
No dedicated community platforms such as Discord or Telegram found.
Detailed pricing information not visible on the main website; requires further inquiry.
Potentially complex for very small teams due to broad feature set.
Qwak's Pricing
| Has free plan | No |
|---|---|
| Free trial details | |
| Pricing model | Paid |
| Is credit card required | No |
| Paid from | 150 USD |
| Has lifetime plan | No |
| Billing frequency | Monthly |
Details of Pricing Plan
Pro
150 USDEnterprise X
950 USD- 125 GB + 1000 ML Credits Base Consumption
- SLA Support | 99.9% Uptime
- Advanced Security
- Package Curation & Catalog
- Globally Federated Repositories
- Enterprise Access Control (SSO)
- Enhanced SCA & Model Security
- AI/ML Lifecycle Management
- AI/ML Serving
- One Platform Experience with GitHub
Enterprise +
0 USD- Custom Consumption
- High Touch Support
- Strategic Multi-year Contracts
- Global Access Federation
- Software Distribution
- Distributed Edge Nodes
- Advanced Traffic Management
- Third Party Evidence Collection
- Multi-cloud and Shadow AI/ML Deployments
- Streaming Feature Store for ML
Pro X
27000 USD- 1 Server
- SLA Support
- Universal Binary Repository
- Release Lifecycle Management
- Enhanced SCA & Model Security
- Complete Container Registry
Enterprise X (Yearly)
48000 USD- 3 Servers
- SLA Support
- High Availability
- Globally Federated Repositories
- Enterprise Access Control (SSO)
- AI/ML Lifecycle Management
- AI/ML Serving
- One Platform Experience with GitHub
Enterprise + (Yearly)
0 USD- 6 Servers
- 24/7 High Touch Support
- Global Access Federation
- Software Distribution
- Distributed Edge Nodes
- Private CDN
- Third Party Evidence Collection
- Multi-cloud and Shadow AI/ML Deployments
- Streaming Feature Store for ML
FAQs of Qwak
Qwak Company Information
Analytic of Qwak
Visit Over Time
Monthly Visits
23.5k
Avg Visit Duration
00:00:16
Page Per Visit
1.69
Bounce Rate
37.67%
Nov 2025 - Jan 2026 All Traffic
Geography
Top 5 Regions
United States
32.51%
India
16.08%
Germany
13.36%
Vietnam
9.68%
United Kingdom
5.36%
Nov 2025 - Jan 2026 Worldwide Desktop Only
Traffic Sources
Search
50.89%
Direct
35.00%
Referrals
7.78%
Social
4.76%
Paid Referrals
1.39%
Mail
0.09%
Nov 2025 - Jan 2026 Desktop Only
Top Keywords
| Keyword | Traffic | Cost Per Click |
|---|---|---|
| ml monitoring tools | 150 | $ -- |
| feature engineering pipelines | 140 | $ -- |
| why do we need feature store | 120 | $ -- |
| quak | 2.6k | $ -- |
| end to end machine learning pipeline | 190 | $ -- |
Qwak Reviews
5/5
Qwak's Main Competitors and alternatives?
- DataRobot
- H2O.ai
- Google Cloud AutoML
- Microsoft Azure ML
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