TrustRadius

Deep Block vs. Vertex AI

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Deep Block
Score 0.0 out of 10
Enterprise companies (1,001+ employees)
Deep Block is a no-code platform to train and use AI models based on Omnis Labs' patented Machine Learning technology. They state Deep Block was created so that individuals and enterprises alike can train their own computer vision models and bring the power of AI to the applications they develop, without any prior programming or machine learning experience. Through its…
$10
per month per user
Vertex AI
Score 8.7 out of 10
N/A
Vertex AI on Google Cloud is an MLOps solution, used to build, deploy, and scale machine learning (ML) models with fully managed ML tools for any use case.
$0
Starting at
Pricing
Deep BlockVertex AI
Editions & Modules
Essential
$10
per month per user
Pro
$100
per month per user
Expert
$300
per month per user
Imagen model for image generation
$0.0001
Starting at
Text, chat, and code generation
$0.0001
per 1,000 characters
Text data upload, training, deployment, prediction
$0.05
per hour
Video data training and prediction
$0.462
per node hour
Image data training, deployment, and prediction
$1.375
per node hour
Offerings
Pricing Offerings
Deep BlockVertex AI
Free Trial
YesYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeNo setup feeOptional
Additional DetailsAll our core features are included with our Essential, Pro, and Expert plans. Only our Enterprise features are available on demand. Pricing differs based on the amount of GPU hours desired each month. A GPU hour is the sum of the duration of each individual GPU that's been used for deep learning. Each time your train your AI or process your raw files to extract predictions from your AI model, Deep Block calculates the time spent processing your information and display it in your billing tab. To estimate the number of GPU hours you would need per month, feel free to contact sales and get an estimate.Pricing is based on the Vertex AI tools and services, storage, compute, and Google Cloud resources used.
More Pricing Information
Best Alternatives
Deep BlockVertex AI
Small Businesses
Google Cloud AI
Google Cloud AI
Score 8.5 out of 10
Google Cloud AI
Google Cloud AI
Score 8.5 out of 10
Medium-sized Companies
Google Cloud AI
Google Cloud AI
Score 8.5 out of 10
Google Cloud AI
Google Cloud AI
Score 8.5 out of 10
Enterprises
Dataiku
Dataiku
Score 8.6 out of 10
Dataiku
Dataiku
Score 8.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Deep BlockVertex AI
Likelihood to Recommend
-
(0 ratings)
8.1
(7 ratings)
Performance
-
(0 ratings)
8.1
(3 ratings)
Configurability
-
(0 ratings)
8.6
(4 ratings)
User Testimonials
Deep BlockVertex AI
Likelihood to Recommend
Deep Block
No answers on this topic
Google
We needed to build some ML models and Vertex AI is one such place where all the functionalities are consolidated for model deployment, tweaking and monitoring. And although it is costly, it is compatible with google cloud services and is scalable which makes it the perfect tool for us.
EL
Edwin Leonard
Senior Software Engineer
Read full review
Pros
Deep Block
No answers on this topic
Google
  • Vertex AI comes with support for LOTs of LLMs out of the box
  • MLOps tools are available that help to standardize operational aspects
  • Document AI is an out of the box feature that works just perfectly for our use cases of automating lots to tedious data extraction tasks from images as well as papers
Verified User
Anonymous
Read full review
Cons
Deep Block
No answers on this topic
Google
  • Customization of AutoML models - A must needed capability to be able to tweak hyperparameters and also working with different models
  • Model Explainability -Providing more comprehensive explanations about how models are utilizing features could be very beneficial
  • Model versioning and experiments tracking - Enhancing the versioning capability could be good for end users
Ekta Shah | TrustRadius Reviewer
Ekta Shah
Associate Data Scientist
Read full review
Performance
Deep Block
No answers on this topic
Google
Vertex AI is very user friendly and it is very fast. We can spin up instances pretty quickly and it allows to work with GPU instances without much planning. Pages load up very quickly and tasks are competed pretty much in time frame. It integrates with other systems also very well.
Ekta Shah | TrustRadius Reviewer
Ekta Shah
Associate Data Scientist
Read full review
Alternatives Considered
Deep Block
No answers on this topic
Google
Vertex AI is much more accessible to non-developers than IBM's product. Moreover, Vertex AI integrates well with other Google products, enhancing its capabilities. A big plus is its integration with cloud storage, that allows for better management and access of data. In all honesty, it wasn't much of a difficult choice to choose Vertex AI.
Verified User
Anonymous
Read full review
Return on Investment
Deep Block
No answers on this topic
Google
  • It consolidated all the functionalities in one place for AI and ML development.
  • Scalable and compatible with google cloud services.
  • Though we can manually allocate resources, it is still very costly.
EL
Edwin Leonard
Senior Software Engineer
Read full review
ScreenShots

Deep Block Screenshots

Screenshot of Data labeling is the foundational block of a good AI model. Deep Block offers an annotating tool.Screenshot of Deep Block lets an unlimited number of users label the same pictures at the same time to synchronize on important projects and avoid duplicated work.Screenshot of Any object, presence of new objects or absence of previously present objects can be detected, and the operator alerted.

Vertex AI Screenshots

Screenshot of an introduction to generative AI on Vertex AI - Vertex AI Studio offers a Google Cloud console tool for rapidly prototyping and testing generative AI models.Screenshot of gen AI for summarization, classification, and extraction - Text prompts can be created to handle any number of tasks with Vertex AI’s generative AI support. Some of the most common tasks are classification, summarization, and extraction. Vertex AI’s PaLM API for text can be used to design prompts with flexibility in terms of their structure and format.Screenshot of Custom ML training overview and documentation - An overview of the custom training workflow in Vertex AI, the benefits of custom training, and the various training options that are available. This page also details every step involved in the ML training workflow from preparing data to predictions.Screenshot of ML model training and creation - A guide that shows how Vertex AI’s AutoML is used to create and train custom machine learning models with minimal effort and machine learning expertise.Screenshot of deployment for batch or online predictions - When using a model to solve a real-world problem, the Vertex AI prediction service can be used for batch and online predictions.