Buy-Side Enterprise Data Management
Govern Buy-Side Data
at Enterprise Scale
Get Started Today
AUM managed using IVP technology
buy-side firms on IVP solutions
Years of buy-side domain expertise
ONE GOVERNED PIPELINE. EVERY SOURCE, EVERY STAGE.
Low-Maintenance Governed Pipelines
Design and scale ETL/ELT data flows using a virtual drag-and-drop interface, with governance, lineage, and an audit trail maintained at every stage.
Automated Data Quality Control
Apply more than 100 preloaded business and technical rules across ingested datasets, and create new rules in plain English through the IVP Data Quality Agent.
Root-Cause Exception Resolution
The Data Quality Agent traces each exception to its source, escalates to the originating system, applies corrections, and re-executes the affected flow within the same workflow.
AI-Powered Document Parsing
The AI File Parser ingests Excel, CSV, PDF, and scanned documents, detects tables and headers regardless of layout, and validates extracted output before it reaches the pipeline.
Natural-Language Pipeline Design
The Pipeline Builder and Documentation Agent builds and refines ETL/ELT pipelines from plain-language instructions, with documentation regenerated automatically as pipelines change.
Audit-Ready Catalog and Lineage
Maintain end-to-end lineage and a governed data catalog that gives operations, compliance, and risk teams one traceable source of truth for how every dataset was transformed, moved, and delivered.
Optimized Reporting Performance
The SQL View Optimization Agent scans SQL views for weak joins, redundant filters, and costly structures, then suggests refactors and indexing recommendations tailored to query patterns and access paths.
Cloud-Native Snowflake Execution
Run ETL on dedicated Snowflake compute isolated from analytical workloads, auto-suspended when idle, with any dataset recoverable up to 90 days back.
Low-Maintenance Governed Pipelines
Design and scale ETL/ELT data flows using a virtual drag-and-drop interface, with governance, lineage, and an audit trail maintained at every stage.
Automated Data Quality Control
Apply more than 100 preloaded business and technical rules across ingested datasets, and create new rules in plain English through the IVP Data Quality Agent.
Root-Cause Exception Resolution
The Data Quality Agent traces each exception to its source, escalates to the originating system, applies corrections, and re-executes the affected flow within the same workflow.
AI-Powered Document Parsing
The AI File Parser ingests Excel, CSV, PDF, and scanned documents, detects tables and headers regardless of layout, and validates extracted output before it reaches the pipeline.
Natural-Language Pipeline Design
The Pipeline Builder and Documentation Agent builds and refines ETL/ELT pipelines from plain-language instructions, with documentation regenerated automatically as pipelines change.
Audit-Ready Catalog and Lineage
Maintain end-to-end lineage and a governed data catalog that gives operations, compliance, and risk teams one traceable source of truth for how every dataset was transformed, moved, and delivered.
Optimized Reporting Performance
The SQL View Optimization Agent scans SQL views for weak joins, redundant filters, and costly structures, then suggests refactors and indexing recommendations tailored to query patterns and access paths.
Cloud-Native Snowflake Execution
Run ETL on dedicated Snowflake compute isolated from analytical workloads, auto-suspended when idle, with any dataset recoverable up to 90 days back.
Experience the IVP Edge
Get a live walkthrough of how IVP Enterprise Data Management governs data from ingestion through distribution, resolves exceptions at their source before they reach downstream systems, and builds production pipelines from plain-language instructions across fund administrators, brokers, and market data vendors.
