CONTINUOUS
DATA TRUST
INTELLIGENCE
Transform passive metadata records into dynamic crystalline trust networks. Automatically score, propagate lineage risks, and deploy code-level tests before faults cascade.
Data compliance decays in silence.
PRAXIS mends the lineage loop.
Static metadata libraries are archives of historical schema facts. They do not prevent drift. PRAXIS intercept data streams, calculates real-time compliance grades, and implements active safety gates at ingestion.
Multi-agent orchestration
Granular auditing
Select an operational dimension to display its calculations, threshold limits, and compliance triggers.
integrity score
88/100Lineage risk propagation
Ingestion decay propagates downstream. A drift warning in an upstream log decodes scores, sending quality warning signals to all downstream analytical nodes.
ML ingestion safety gates
Evaluate training datasets. Before pipeline runs trigger training, the ML gate checks composite compliance. If upstream trust decays below parameters, execution is blocked.
Automated test synthesis
PRAXIS generates code-level test configurations to patch validation gaps. It compiles schema contracts and opens a GitHub PR to fix the broken parameters.
"Field 'logging_events.user_id' type has changed from VARCHAR to INTEGER upstream. Dependent asset 'order_details' carries VARCHAR expectations."
The executive briefing
"Today, 4 out of 8 domains maintain full green compliance parameters. 12 datasets require review due to propagated upstream lineage warnings. 2 remediation branches have been opened on GitHub to address these gaps."
Editorial briefings
PRAXIS digests metadata changes into a human-readable summary, giving clear operational insight instead of raw logging lists.
Begin active orchestration
Enter the central operational room to inspect running agents, query the ML training safety gate, and view live metadata audits.