One platform. Every dimension of data trust.
Qelvora unifies observability, quality, and context so your team always knows the state of your data and can do something about it.
Observe → Score → Explain → Resolve
Four steps. One unified workflow for data trust.
Know when your data breaks
Agentless monitoring across freshness, volume, schema, and cost. ML anomaly detection fires before downstream consumers notice anything is wrong.
Measure quality at every level
No-code rule authoring with AI recommendations. Quality scores at column, table, and business-domain level, always fresh, always visible.
Give data meaning and context
Automated discovery, classification, and tagging. A living business glossary and semantic lineage map so anyone can find and trust the right data.
Fix issues fast with full context
Column-level lineage and impact analysis so you know exactly what broke, who is affected, and what to fix first, every time.
Up and running in minutes
Agentless connectors map your stack in minutes.
ML baselines every table, column, and pipeline automatically.
Quality scores and SLAs travel with the data.
Prioritized incidents with root cause, impact, and auto-remediation.
See everything. Miss nothing.
Qelvora provides continuous, agentless observability across every data source in your stack: warehouses, lakes, databases, and streaming systems. Self-learning thresholds adapt to your data patterns over time, surfacing only real incidents and eliminating alert fatigue. Lineage-aware routing ensures alerts go to the right owner with the right context.
Quality your business can see.
Author quality rules without writing a single line of SQL. Qelvora's AI recommends rules based on your data profile, and scores roll up from column to table to business domain so executives and data stewards see the same quality signal. Rules are version-controlled, tested, and auditable.
Make every data asset discoverable.
Qelvora automatically discovers, classifies, and tags assets across your entire estate. The built-in business glossary maps technical fields to business terms, and semantic lineage traces every metric back to its source. Context is always up to date with no manual cataloguing required.
Connects to your entire stack
40+ native integrations. No custom code required.
Frequently asked questions
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