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gathr.ai

Score8.8 out of 10

11 Reviews and Ratings

What is gathr.ai?

Gathr.ai powers AI with complete data context for higher quality intelligence. Product suite: Data Warehouse Intelligence | Document Intelligence | System Intelligence | Data Pipelining | Data+AI Fabric | Analytics

Media

the interface to build AI applications
the GathrIQ Data+AI Copilot
GenBI
where to visualize data and generate insights automatically

1 / 5

Top Performing Features

  • Simple transformations

    Simple data transformations are calculations, data type conversions, aggregations and search and replace operations

    Category average: 8.8

  • Complex transformations

    Complex data transformations are data normalization, advanced data parsing, etc.

    Category average: 7.3

  • Business rules and workflow

    Ability to define and manage business rules and workflows

    Category average: 8.1

Areas for Improvement

  • Collaboration

    Collaboration is enabled by a shared repository of project information and metadata

    Category average: 7.8

  • Testing and debugging

    Tool to debug and tune for optimal performance

    Category average: 7.1

  • Connect to traditional data sources

    Ability to connect to traditional data sources like relational databases, flat files, XML files and packaged applications

    Category average: 8.8

Keeps our pipelines resilient

Use Cases and Deployment Scope

Before working with gathr.ai, we had every kind of data issue—drift, late events. gathr.ai made our pipelines resilient without overengineering.

Easy to create data engineering pipelines. gathr.ai has reduced manual efforts of creating Data pipelines. Using multiple data sources, we are able to process and ingest data to the respective emitters.

Pros

  • With fewer pipeline failures and shorter debugging cycles, we can spend more time innovating and tackling certain use cases we didn’t have time for earlier.
  • Easier to orchestrate scheduled batch pipelines using Apache Airflow component.

Cons

  • No deal breakers yet. There's could be more learning material available online though.
  • Session connection can be made more faster without frequent disruption.

Return on Investment

  • It has enhanced overall productivity of our team.
  • Reduced manual efforts of creating and scheduling ETL pipelines.
  • Multiple data sources and connectors at one place.

Usability

Vast selection of built-in connectors

Use Cases and Deployment Scope

We use Gathr.ai primarily for data integration across a variety of source systems— internal databases, SaaS applications, marketing tools, etc. The goal is to bring all this data together in one place to power multiple downstream use cases. The platform’s comprehensive library of connectors has saved our engineers a lot of time and supported our pipeline development efforts.

Pros

  • Gathr.ai offers a vast collection of built-in connectors allowing us to pull data from diverse sources like Salesforce, HubSpot, and MySQL.
  • Its ability to ingest large volumes of data smoothly is commendable.
  • The drag-and-drop visual canvas helps build data integration pipelines effortlessly.

Cons

  • So far we’ve had a smooth experience with the tool and have gotten timely responses from the support team as well.

Return on Investment

  • Our engineering team has saved substantial time and effort by using their built-in data connectors.
  • Business users now get access to clean, integrated data faster, improving time-to-insight for key use cases.
  • Runs concurrent workflows and delivers predictable price-performance.

Usability