Clarifai Alternatives | Fritz AI

Clarifai vs. Fritz AI Studio

Mobile Machine Learning Technology Comparison
 

Many engineers who are looking for an ML provider for their mobile project consider Clarifai, which is a model building and deployment platform designed for ML teams working through the full ML project lifecycle. With in-app tools for data labeling, modeling, and ground-truth data collection, Clarifai’s Portal includes the functionality to build and deploy custom models. Clarifai also includes a range of pre-built models for a variety of business and industry use cases. While Clarifai includes a mobile SDK to incorporate models in iOS and Android apps, Clarifai is primarily designed for cloud-based deployment.

Fritz AI Studio is a machine learning platform built specifically for iOS and Android developers who may not have an ML background. Customers use it to generate and collect labeled datasets, train optimized models without code, deploy and manage on any mobile platforms, and improve models and app UX based on real-world data.

Download the Mobile Machine Learning Technology Comparison Guide

This free guide compares six different ML providers: Amazon SageMaker, Firebase ML, TensorFlow Lite, Create ML, Clarafai, and Fritz AI. See how each provider compares across data management, model training and management, deployment, model iteration, and more.

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Clarifai vs. Fritz AI Product Specs

DATA

FRITZ AI

CLARIFAI

Data Generation

✅ Labeled synthetic data generation

❌ Synthetic data generation not supported

Data Upload

✅ COCO dataset bulk upload; zip file upload; individual image upload

✅ Manual data upload

Data Labeling

✅ In-app labeler:

  • Image Labeling
  • Object Detection
  • Image Segmentation
  • Pose Estimation

✅ In-app labeler:

  • Classification
  • Bounding box (object) detection
  • Polygon detection

Data Export

✅ Export labeled dataset snapshots

❌ Not supported

MODEL TRAINING

Model Training Interface

✅ No-code

✅ No-code for pre-built (for custom models, coding is involved)

Advanced Configurations

✅ Fine-tune model inputs and outputs, configure performance requirements, and more

✅ Add or remove concepts/tags to models as you build

Mobile-Specific Optimizations

✅ Use-case-based model variants; mobile-optimized model architectures

✅ Use-case-based model variants

MODEL MANAGEMENT

Model Types Supported

✅ Core ML (iOS); TensorFlow Lite (Cross-platform); SnapML (Snapchat)

✅ Core ML (iOS); TensorFlow Lite (Cross-platform)

Model Versioning

✅ Keras/Model checkpoints;

✅ Model version IDs

Model Protection/Encryption

✅ Model encryption available

❌ Model encryption unavailable

MODEL DEPLOYMENT

Model Pre- and Post-Processing

✅ Built-in processing with Fritz SDK

✅ Built-in processing with Clarifai Mobile SDK

Platforms Supported

✅ iOS, Android, Snapchat

✅ Android & IOS

MODEL RETRAINING & ITERATION

Ground-truth Data Collection

✅ Automatically collect and label real-world data, and (re)train models on it

✅ Automatically collect and label production model data, and (re)train models on it

Model Iteration

✅ Model checkpoints

✅ Model versioning

Model Updates

✅ Over-the-air model downloads

✅ Over-the-air model downloads

PRICING & PLANS

Free Tier

✅  Permanent with monthly global usage limits; 14-day free trials for all paid subscription plans

✅ 5,000 free operations per month

Pricing Structure

✅  Subscription-based pricing

✅ Pay-as-you-go model licensing

SUPPORT

Available Support

✅  Plan-based support includes: Community forum, Slack, email, phone, and dedicated success manager

✅ Chat & online forum, Slack Community

Download the Mobile Machine Learning Technology Comparison Guide

This free guide breaks down the top mobile ML technologies and reviews them based on key components:

  • Data capabilities
  • Model training, management, and deployment
  • Model retraining and iteration
  • Pricing and support options

This guide offers product specs for Amazon SageMaker, Firebase ML, TensorFlow Lite, Create ML, Clarafai, and Fritz AI to help you decide which platform is best for your project.