Evidalio - Data Impact Intelligence

Evidalio is a data impact intelligence platform that helps organizations translate data reliability events into business and financial context. It correlates observability signals, lineage, asset identity, ownership, and governed assumptions to create prioritized Issues, estimate blast radius, and model potential operational or monetary exposure. The result is a shared, traceable view that helps data teams explain technical conditions in terms that CTOs, CFOs, and business stakeholders can act on.

Evidalio complements existing data platforms rather than replacing them. Its configurable integration framework supports metadata, lineage, execution, quality, and observability patterns for technologies such as AWS Glue, Amazon Redshift, dbt, OpenLineage, Apache Airflow, Databricks, Snowflake, Informatica IICS, Azure Data Factory, BigQuery, Power BI, DataHub, OpenMetadata, Great Expectations, Soda, and MLflow. Availability and depth vary by connector, and third-party products may require separate subscriptions, licenses, and configuration.

Governed workflows provide fine-grained role-based access, Issue assignment, audit history, assumption extraction, and approval, value simulation, approved-assumption recalculation, and evidence-pack generation. Optional AI-assisted capabilities can identify candidate assumptions from documents, correlate technical and business signals, and generate reviewable narratives. Human approval and execution boundaries keep financial models and downstream actions based on authorized inputs.

The included MDM and CRM journey is a sample reference use case demonstrating how a data condition can be detected, correlated, assessed, governed, and communicated. Evidalio can be configured for other domains, assets, business processes, and value models.

Product highlights:

1. Translate data reliability signals into governed business and financial impact using lineage, ownership, assumptions, and configurable value models.
2. Prioritize Issues through automated correlation and blast-radius analysis, with assignment, approvals, audit history, and evidence generation.
3. Bridge CTO and CFO decision-making with transparent assumptions, scenario-based value simulation, and traceable impact narratives.

Primary use cases:

Data reliability impact assessment: Correlate data quality, execution, freshness, lineage, and platform signals to identify affected assets, business processes, owners, and downstream consumers.

Financial exposure modeling: Apply approved assumptions and configurable value models to estimate potential revenue exposure, productivity loss, remediation cost, SLA impact, or other customer-defined measures. Results are decision-support estimates, not accounting records or guaranteed financial outcomes.

Governed Issue management: Create, assign, investigate, and resolve Issues with ownership, status, evidence, audit history, and role-based access controls.

CTO-to-CFO communication: Create a common narrative connecting technical reliability, operational consequences, investment priorities, and financial considerations.

Assumption governance: Extract candidate assumptions from supported documents, route them for review, approve or reject them, and permit recalculation only after approval.

Data-estate integration: Add a configurable impact layer over cloud, warehouse, transformation, orchestration, catalog, observability, BI, and ML platforms without replacing those systems.

Capabilities:

• Configurable event-ingestion and processing pipeline
• Cross-source asset identity resolution and reconciliation
• Business-context and ownership mapping
• Observability-signal correlation and automated Issue creation
• Issue lifecycle, assignment, and audit history
• Blast-radius and downstream-impact analysis
• Governed assumptions and approval workflows
• Candidate-assumption extraction from supported documents
• Scenario-based value simulation
• Approved-assumption recalculation boundary
• Evidence-pack generation
• Fine-grained users, roles, and permissions
• Configurable connector and secret-provider framework
• Optional AI-assisted correlation and narrative workflows
• Docker-based deployment with Terraform automation for AWS