Most enterprises do not lose to competitors because they lack data. They lose because that data sits in systems that refuse to talk to each other. A finance tool here, a warehouse platform there, a CRM that exports to nobody. The cost shows up quietly. Reports take days instead of minutes, teams argue over whose numbers are right, and AI
A single bad value can sit in a production table for weeks, spreading into dashboards, models, and decisions downstream before anyone catches it. Gartner pegs the average cost of poor data quality at $12.9 million a year per organization. Most of that traces back to maintenance that never ends. Pipelines break on an upstream schema change, and models drift while serving confident,
Most engineering teams running AI agents juggle four or five at once and spend a meaningful chunk of time copy-pasting output between them. Each agent runs in its own silo with no awareness of what the others are doing. Databricks built Omnigent to solve that. Released in June 2026 under Apache 2.0, it introduces a new category called the meta-harness. This
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