DQC

Set the goal.AI powers the execution.

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Trusted by

  • EnBW
  • GASAG
  • Porsche Holding
  • Balluff
  • J&J MedTech
  • msg systems
  • Valora
  • Crowe
  • Wiener Börse
  • Curacon
  • Herose
  • dataspot.
  • ETL
  • IOP

The leading agents for AI-ready data

Rules, agents, and continuous learning, all running on your existing stack.

DQC works in three loops: detect drift and propose rules, autonomously remediate issues, and learn from every commit. You stay in control: every change is reviewable before it touches production.

01Detect & Propose

Rules that write themselves for your data

DQC continuously profiles your tables, finds the rules you forgot to write, and proposes them with the evidence to back each one. You stay the editor: review, refine, reject.

  • Pattern mining: every column profiled against 30+ check families
  • Evidence-first: each suggestion shows the data, not just a recommendation
  • Auditable: every rule traces back to who or what proposed it
3 new data quality rules found
The Assistant analyzed your data patterns and identified missing checks to ensure long-term data reliability.
×
Phone Number Format94% confidence

Detected inconsistent formatting in the 'phone' column. Standardizing to E.164 ensures reliability for automated communication workflows.

DismissAccept
Address Completeness91% confidence

Found 23% of records with missing zip codes in 'shipping_address'. This rule ensures mandatory completeness for postal routing.

DismissAccept
Revenue Outlier Detection87% confidence

Identifies statistical anomalies in financial values. This rule flags entries exceeding 3 standard deviations to prevent manual entry errors.

DismissAccept
Dismiss allAccept all
bid_number3
uniqueTests if entries are unique.Active
mandatoryTests for missing values, e.g. NULL, 'NA', 'TBD'.Active
outlierTests for abnormally high or low values.Active
order_date2517 issues
mandatoryEnsures every order has a recorded timestamp.Active
range_checkFlags dates in the future or before platform launch.Active
order_id2
uniqueEnsures each transaction has a distinct identifier.Active
mandatoryPrevents records with missing order identifiers.Active
02Autonomous remediation

Specialized teammates that improve your data

Chat with the DQC Assistant, or let it message you. When something breaks, it traces upstream, drafts a fix, and waits for your decision before moving forward.

  • Proactive: pings you before downstream reports do
  • Grounded: every plan cites the rows, the rule, the upstream system
  • Reversible: sandbox-first writes, one-click rollback
DQC Assistant
Watching 412 rules · 150 tables
Online
DQC Assistant14:08
EU3 sales stopped reporting: 4,217 orders with country_code = NULL since 14:02. Looks like a failed IDoc batch. Want me to investigate?
JB
Johannes14:09
Yes, please look into it.
DQC Assistant14:09
Found it: BATCH/9912 failed after a schema change in VBAK. I can re-derive the country codes and replay in sandbox first.
Proposed fix
· sandbox first
Re-derive country_code from billing address
Replay BATCH/9912 in sandbox first
Notify revenue team on commit
Estimated · €84,200 restored
Apply fix
Ask the assistant…⌘ K
03Continuous learning

The only constant is change. Your rules adapt with it.

Markets expand, suppliers change formats, regulations shift. DQC watches every check's signal, spots drift, and proposes the configuration change with a diff you can apply in one click.

  • Drift detection: statistical and categorical, per rule, per column
  • Diff-based config: see exactly what changes before you commit
  • Outcome tracking: every applied change reports its impact back
rulesCountry validationActive
Description

Validates that the country column contains only approved values for international shipping and tax calculations.

Valid categories
GermanyAustria+ Add
Columns scoped
orders.countryshipping.country
Valid sample
DE14,832
AT2,108
Issue sample
FR14 records
FRA3 records
Quality trend · 30 days
Pass rate83%
Valid
83%
16,940 rows
Issues
17%
3,471 rows · mostly FR
Configuration Suggestion
AI detected 17 new records with ‘France’ in your dataset. Adding this to the valid categories will resolve 17% in false positive issues.
×
Current configuration
GermanyAustria
Suggested configuration
GermanyAustriaFrance
DismissApply Update

Integrations

Works where your data is.

Sources
  • SAP S/4HANA
  • Snowflake
  • Databricks
  • BigQuery
  • PostgreSQL
  • Salesforce
DQC Platform
DQC
Agents
2.4M
entries improved
Outcomes
  • AI-ready data
  • 1-2% lost revenue recovered
  • 23x faster time-to-market
  • >80% automated BP corrections
  • Domain experts in control
Made in GermanyIntegrated AIGDPR compliant

Connector catalog

Browse the full connector list

Data systems · Catalogs · PIMs · BI · Communication · Files · APIs

SAP S/4HANASAP S/4HANAData systems
SnowflakeSnowflakeData systems
DatabricksDatabricksData systems
BigQueryBigQueryData systems
PostgreSQLPostgreSQLData systems
SalesforceSalesforceAPIs
Apache KafkaApache KafkaData systems
dbtdbtData systems
Azure SynapseAzure SynapseData systems
SQL ServerSQL ServerData systems

DQC Platform

Monitor and improve your enterprise data automatically. Secure. Flexible. Effective.

<1 week

Time to set up

2 weeks

Time to first impact

>13x

Return-on-Investment

Let's write your success story together.

Book your strategic consultation today.

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