Eliminate silent data failures before they impact your business.
xDQ validates and flags bad data before remediation costs spiral, safeguarding the integrity of your downstream analytics and business value.
xDQ combines AI-assisted rule creation with real-time alerting and validation that runs entirely inside your own cloud, so bad data gets caught before it reaches your stakeholders.
Schedule validations or run them on demand. Track quality trends across every run and see the health of all your data assets from a single dashboard. When a rule fails, receive alerts through email, Slack, or Microsoft Teams, so issues get fixed before anyone downstream notices.
Learn MoreMeet Xonic: xDQ’s AI assistant. Ask questions about your data quality in plain language and get instant answers. Xonic also analyzes metadata and suggests the right quality rules automatically, so your team spends minutes building coverage.
Learn MoreWork with cloud-based tabular and file data sources you already own in a few clicks. XDQ validates data where it lives: inside your cloud infrastructure with zero data egress, so sensitive data never leaves your environment while every asset stays covered.
Learn MoreOur team brings hands-on expertise across data governance, data architecture, AI, and data analytics; whether you’re extending xDQ or tackling a data challenge independently.
We help you govern data with confidence; from ownership and stewardship frameworks to master data management, cataloguing, lineage, and security. The result: data your organization can trust, track, and act on with confidence.
Learn MoreFrom embedding AI into your data architecture to building Generative AI solutions, autonomous agents, and AI-augmented data strategy, Xovate helps you embark on the AI journey. The result: systems that don’t just report on your business but actively work for it.
Learn MoreWe build the pipelines your data runs on: from engineering, ETL/ELT, and automation to data virtualization and real-time streaming analytics. The result: your data lands where it needs to be, in the shape your business actually uses.
Learn MoreWe design industry-standard data models and modern Data Vault warehousing, backed by hands-on strategy and mentoring from experienced practitioners. The result: an architecture your analytics can actually scale into.
Learn MoreWe design, migrate, and implement cloud analytics solutions. The result: lower overhead, more flexibility, and analytics built for whichever major cloud platform you run on.
Learn MoreWe design dashboards, enable self-service analytics, and deploy enterprise BI, made useful by hands-on training, so your team uses it. The result: data your whole organization can explore, not just your analysts.
Learn MoreWhat building your own data quality checks really costs your team.
| xDQ Platform | AI Vibe-coded DQ Checks | |
|---|---|---|
| Data Quality Coverage | Rule library, all assets | Only what is coded |
| Data Observability | AI-powered bot monitors 24/7 and explains | Alerting, scheduling and CI still to build |
| Enterprise Data Health View | One dashboard for every source, asset and team | Results scattered across scripts and repos |
| Cost | LowSee plans → | Medium–High |
| Deployment Ease | Live in minutes | Easy first cut, difficult to productionise |
Running xDQ in your own cloud? Get an instant estimate.
*Prices exclude GST.AI vibe coding, build: prompts × minutes per prompt + review and test hours + deploy and integrate hours = engineer hours; × hourly cost, plus AI tokens (prompts × tokens per prompt × price per million; Claude Sonnet 5.5 API at US$2 input and US$10 output per million tokens, blended for prompts that are mostly input, in A$).
AI vibe coding, upkeep: upkeep hours a month × 12 (schema changes, false alarms, fixes).
xDQ: setup hours, plus rule tuning hours a month × 12, at the same hourly cost, plus a year of Assure at the monthly price on the Pricing page (12 × monthly, billed annually, after a free first month). The platform itself is maintained by Xovate. Prices exclude GST.
These are estimates from the numbers above, not measured customer results.
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