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Appomate vs Continual

Appomate or Continual? A Comprehensive Review

Appomate

Appomate

Transform your life and work with custom-built AI apps and agents

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Continual

Continual

Cloud-based predictive modeling using SQL.

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Overview

Description

Appomate is a powerful platform that empowers users to enhance their daily lives and work processes with the help of custom-built AI apps and agents. With this platform, users can easily

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Continual is the go-to operational AI platform for predictive modeling in the cloud. It simplifies the process of building and maintaining models by using SQL and dbt declarations,

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Pricing Options

  • No free trial
  • $99, month
  • No free trial
  • Not Available
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Features

Total Features

Features
Features

Unique Features

No features

No features

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Pricing

Pricing Option

      Starting From

      • $99, month
      • Not Available
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      Other Details

      Customer Types

      • No customer type information available
      • No customer type information available
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      User Reviews

      User Ratings

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      Pros

      • Adaptable workflow setup

      • 'Try before you buy' feature

      • Sandboxed testing environment

      • Post-payment app deployment

      • Dashboard / public URL access

      • Seamless website integration

      • Free lifetime support

      • Revenue-sharing feature

      • User requirement capturing

      • Different pricing plans

      • Cloud-based predictive modeling

      • Uses SQL for app creation

      • Works with BigQuery

      • Snowflake

      • Redshift

      • and Databricks

      • No need for complex infrastructure

      • Models improve continually

      • Data and models stored on warehouse

      • Easily accessible to operational and BI tools

      Cons

      • Requires prior definition of needs

      • Dashboard access needed

      • Undefined timeframe for development

      • Charges for storage and bandwidth

      • Limited Support - 1-3 business days

      • High upfront pricing

      • Weak data usage transparency

      • Only usable after payment

      • Limited application formats

      • Restrictions on embedding

      • SQL-centric

      • Limited to cloud data platforms

      • Dependency on modern data stacks

      • No MLOPS infrastructure

      • Limited extensibility (Python only)

      • Dependent on dbt compatibility

      • Not suitable for traditional data management systems

      • Data must be on the same warehouse

      • No mention of multilingual support

      • Dependent on continuous access to data warehouse

      Media and Screenshots

      Screenshots

      Appomate
      Continual

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      Disclaimer: This research has been collated from a variety of authoritative sources. We welcome your feedback at [email protected].

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