Enforce Data Quality
at the Source

Address data quality issues proactively early in the data lifecycle, consistently and at scale.

Address data quality issues proactively early in the data lifecycle, consistently and at scale.

Address data quality issues proactively early in the data lifecycle, consistently and at scale.

Trusted by data-driven companies

Trusted by data-driven companies

Stop Waiting for Data to Break Things

Poor data quality costs time, trust, and money. Most tools try to fix things after the damage is done. Conduktor Trust enforces data quality where streaming starts—before it enters your pipelines—so issues are detected early and are stopped in their tracks.

Without Trust in Your Data

Data teams discover quality issues days later.

Developers carry the burden of governance.

AI models train and make predictions on broken data.

Analytics and other systems run on polluted streams.

With Conduktor Trust

Quality can be enforced before the data flows.

Visibility is centralized across teams.

AI training and inference are protected from bad data.

Analytics and business systems run on clean, trusted data.

Analytics and business systems run on clean, trusted data.

Why enterprises choose Trust

Enforce policies at the edge
—not in postmortems.

Prevent bad data at ingestion across schema and schema-less topics.

Unify quality, observability, and control—without developer friction.

How it Works

01

Define Rules

Set quality rules—powered by the Common Expression Language (CEL)—to ensure conformance and consistency in data.

Set quality rules—powered by the Common Expression Language (CEL)—to ensure conformance and consistency in data.

Set quality rules—powered by the Common Expression Language (CEL)—to ensure conformance and consistency in data.

Set quality rules—powered by the Common Expression Language (CEL)—to ensure conformance and consistency in data.

02

Apply Policies

Choose where rules apply—regular expressions or specific topics.

Choose where rules apply—regular expressions or specific topics.

Choose where rules apply—regular expressions or specific topics.

Choose where rules apply—regular expressions or specific topics.

03

Trigger actions

Decide what happens when a violation occurs: report, alert, or block data in real-time.

Decide what happens when a violation occurs: report, alert, or block data in real-time.

Decide what happens when a violation occurs: report, alert, or block data in real-time.

Decide what happens when a violation occurs: report, alert, or block data in real-time.

04

Gain insight

Track how often violations occur to prioritize fixes and improve data quality over time.

Track how often violations occur to prioritize fixes and improve data quality over time.

Track how often violations occur to prioritize fixes and improve data quality over time.

Track how often violations occur to prioritize fixes and improve data quality over time.

Informs / Feedback Loop

rules

How the data
is validated

Quality Rule: size (customerId) == 10

Quality Rule: size (customerId) == 10

Quality Rule: size (customerId) == 10

Preset rule: Enforce Avro

Preset rule: Enforce Avro

Preset rule: Enforce Avro

Policies

Where the rule(s)
are applied

Topic: orders

Topic: orders

Topic: orders

Topic: returns

Topic: returns

Topic: returns

Labels: [PII], [GDPR]

Labels: [PII], [GDPR]

Labels: [PII], [GDPR]

actions

What happens if the rule(s)
are violated

Report (Scrutinise)

Report (Scrutinise)

Report (Scrutinise)

Mark (Modify)

Mark (Modify)

Mark (Modify)

DLQ (Dead-Letter Queue)

DLQ (Dead-Letter Queue)

DLQ (Dead-Letter Queue)

Block (Enforce)

Block (Enforce)

Block (Enforce)

insight

Determine the frequency
of violations

Evaluations: 100

Evaluations: 100

Evaluations: 100

Violations: 3

Violations: 3

Violations: 3

What Makes Trust Different?

Most observability
tools sit downstream.
We don’t.

Producer-led enforcement
(Data Contracts)

Reactive Approach
(Monte Carlo)

Conduktor Trust

Works natively on streaming data

Proactively enforces data quality

limited

limited

Supports schema-less topics

Centralized policy control + local enforcement

limited

Ready to Improve the Quality of your Data Streams?

Data quality doesn’t wait. Neither should you.

Ready to Improve the Quality of your Data Streams?

Data quality doesn’t wait. Neither should you.

Ready to Improve the Quality of your Data Streams?

Data quality doesn’t wait. Neither should you.

Ready to Improve the Quality of your Data Streams?

Data quality doesn’t wait. Neither should you.