Karsient Veriq
From Data Quality to Data Trust.
Veriq sits across your existing data platforms and continuously understands, protects, governs, and improves data as it moves — so problems are contained and explained before they reach the business, not discovered after.
Targeted Challenges
Critical Problems Veriq Solves
Bad data travels through the platform undetected until it hits a dashboard or a decision
A single bad record can stop an entire pipeline instead of just the records that need attention
Thousands of failures get investigated one by one instead of as a single root cause
Rule engines require constant manual upkeep as data and sources evolve
Executives have no single, trustworthy view of enterprise data health
Under The Hood
Inside the Data Trust Layer
Veriq doesn't wait for a nightly job to fail. It evaluates data continuously as it moves through your platform, using a decision framework that treats every record on its own merits rather than pass/failing an entire batch.
Every record is scored against layer-aware expectations — Bronze checks ingestion integrity and schema drift, Silver checks standardization and referential integrity, Gold checks business rules and KPI accuracy
The Trust → Pass → Warn → Quarantine → Remediate → Revalidate → Release framework decides the outcome per record, not per batch
When failures spike, the Quality Intelligence Graph traces them back to a single upstream cause — a schema change or source defect — instead of surfacing thousands of unrelated alerts
Veriq Copilot turns that root-cause analysis into a plain-language answer a data steward can act on without paging an engineer
Comprehensive Feature Matrix
Veriq Connect
Universal, configuration-driven connectors for Databricks, Snowflake, Azure, AWS, Spark, Kafka, dbt, and orchestration platforms — attach without a pipeline redesign.
Veriq Observe
Continuous profiling, monitoring, and anomaly detection that adapts its expectations to Bronze, Silver, and Gold layers automatically.
Veriq Govern
Rules, policies, ownership, lineage, and a full audit trail — governance by design, not bolted on afterward.
Veriq Quarantine
Record-level containment that turns every failure into an investigable incident, not a silent rejection.
Veriq Copilot
A conversational AI data-steward assistant that explains failures with evidence and root cause, not just an alert.
Veriq Resolve
Deterministic fixes execute automatically within policy; governed fixes route to a human for approval.
Veriq Replay
Repaired records are revalidated through the same quality controls before re-entering the trusted layer.
Veriq Command Center
An executive data-intelligence view of enterprise Data Trust Score, incidents, and resolution trends.
AI root-cause intelligence
Correlates thousands of failures back to a single upstream schema change or source defect.
Quality Intelligence Graph
Connects source, pipeline, dataset, column, rule, failure, and remediation into one queryable graph.
Adaptive quality intelligence
Proposes candidate quality expectations from historical data and past incidents — AI proposes, governance approves.
Data Trust Score
A multi-dimensional score across accuracy, completeness, consistency, freshness, and business impact, drillable to record level.
Supported Technologies & Platforms
Integrates directly into your existing cloud infrastructure, code repositories, and lakehouse platforms.
DATABRICKS
SNOWFLAKE
FABRIC
AZURE
AWS
GOOGLECLOUD
SPARK
KAFKA
SQL
DBT
AIRFLOWFrequently Asked Questions
Technical Questions About Veriq
No — Veriq is a plug-and-play quality layer. A data engineer attaches it to an existing pipeline through configuration and starts receiving quality intelligence immediately.
Deploy Veriq in your environment
Talk with a technical solutions engineer to scope an assessment, evaluate sample logic, or schedule a sandbox walkthrough.