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AI Powered Adaptive Data Importer

Automate data cleaning of file drops

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Big data is not a problem; bad data is

Can you trust the data you are receiving? Is it accurate, complete, and consistent?

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Your decisions are only as good as your data

Data can go wrong in a million ways. Stop playing whack-a-mole.

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Finding and fixing data issues manually is a pain

Do you find what was missed?

Incoming external data may change without notice

You don't have control over incoming files

Incoming data structures, field names, and data formats can change frequently and without any notice
The average company loses 12% of its revenue due to poor data according to Experian
$3 trillion dollars is the cost of bad data to the U.S. economy each year according to Forbes

Why re-invent the wheel?

Custom file ingestion pipelines are brittle and take a lot of valuable engineering time to maintain.

Anything that can go wrong, will go wrong.

It is a never ending game of patching holes in the system.

A better way: Qluster Adaptive Data Import

  • Connections

    Automatically detect new files from your vendors or simply drop the file into Qluster.

  • Training

    Start by giving Qluster you clean data so it can create an internal model of how your good data should look like. Qluster uses statistics and machine learning to profile and learn from your data. You can also define custom validation rules through the UI.

  • Intelligent Matching

    Qluster uses AI to automatically match the new incoming data to your existing data. You can always decide to add new fields here when needed.

  • Data Quarantine

    Once Qluster is trained, it will stop and quarantine the bad data from entering your system. You can review the bad data at your convenience and fix it. Both sender and receiver of data are enabled to log in and see what went wrong.

  • Observability

    Qluster aggregates similar data issues together and notifies you through Slack, email, or other means when your attention is needed. It provides the 360 degree picture of what is going on and who did what when.

  • Data Lineage

    Qluster tracks how data is modified as it gets cleaned. Every value modification is recorded, along with why and who changed it.

  • Security As A First Class Citizen

    Qluster follows the industry's highest standards when it comes to the security of your data. Files are encrypted as soon as they are picked up from the sources. Qluster does not hold on to your data. You can even host Qluster's settings in the hosted deployment. Logs of data are constantly wiped out to make sure no traces of data are left within our systems.

Qluster is brought to you by the creator of DeepDiff

We create solid data tools. DeepDiff has over 12 million monthly downloads.

Easy setup, highly scalable

Whether on the cloud or in an isolated environment on-prem, we have you covered.

Qluster SaaS currently supports Google Cloud and AWS. Microsoft Azure support is coming soon.

Qluster Enterprise can be deployed on any cloud provider.

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More doing, less data firefighting

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Learns

Qluster uses statistics and machine learning to profile and learn from your data.

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Adapts

Qluster adapts data structures to the incoming data so you don't have to predefine schemas if you don't want to.

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Cleans

Qluster shifts the burden of data cleaning from solely being the receiver's responsibility to a collaborative process between the two parties.

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Reliable recurring data import

Let us solve your data ingestion problems so you can focus on what matters most to your business.

Network effect


By aggregating data issues, we enable individual users to solve similar problems for the rest of the community in the same industry.

Easy to use

Qluster's goal is to be the easiest intelligent data ingestion tool for structured or semi structured data, i.e csv, ljson, or parquet files.

Advanced API

Qluster Enterprise (on-prem deployment) allows validation code in any language to be run via Docker images providing the ultimate freedom to do what you need to do.

Are you ready to see Qluster in action?

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