The Data quality agent checks that the numbers everyone else uses are sound.

It reads every connected source, checks freshness and joins, and flags any break it finds. Your team decides how to fix it.

Every table checked, every join validated.

  • Freshness

    It checks every table in your connected sources for freshness. A source that runs slow is named, with how old its data is.

  • Joins

    It validates the joins between your systems, from orders to invoices to payments. Where two systems should agree, it checks that they do.

  • Breaks, flagged

    A stale table or a join that stops matching is flagged as a break. It names the source the break came from.

  • Cleared for the day

    When every check passes, it clears the sources for the day. The numbers everyone else uses are known to be sound.

Data qualityExample

Sources

all healthy
  • Freshness96 tables checked
  • Joins41 validated
  • BreaksNone found

Cleared the sources for the day

An example with sample data for a fictional company. Its names and figures are not customers or results.

Runs in your cloud.

From every source to your team, inside your own AWS account.

Your company
  • Every connected source
Your AWS account
Data qualityon Amazon Bedrock
  • Flagged breaks
  • Cleared sources
Your team
Nothing leaves.
Data quality reads every connected source inside your AWS account, and hands flagged breaks and cleared sources to your team. Nothing leaves your company.

Read-only access

Your systems stay where they are. You grant the access, and you can revoke it at any time.

Your team decides

The agents draft and flag. Nothing changes until someone approves it.

On the record

Every action the agents take is logged in your own CloudTrail.

Six agents, working on your account.

Everything starts here.

A 30-minute call about your business. No pitch.