Modernize[IQ]

• High database licensing and support costs – restricting investment in innovation and cloud strategy

• Slow, manual PostgreSQL modernization assessments – leading to longer delivery timelines and slower time to value

• Complex PL/SQL and T-SQL codebases – with thousands of procedures and functions, creating uncertainty around scope, risk, and remediation effort

• Long, high-risk modernization timelines – reducing business case confidence to proceed

• Offline data migrations suffering extended downtime – introducing operational disruption and business risk

• No rollback or fallback capability during cutover – increasing operational risk and migration risk 

• Manual, error-prone schema and code remediation – consuming internal resources, diverting teams from strategic initiatives

• Unpredictable tooling costs –  driven by cores, instances, or consumption metrics, making cost forecasting difficult 

Modernization Assessments at Scale

• GenAI-driven modernization assessments

• Assess hundreds of databases per day with automated analysis

• Automated discovery of schema complexity, code patterns, and migration risk

Schema Conversion

• Automated schema conversion from Oracle and SQL Server to PostgreSQL

• Target compatibility for:

  • Open-source PostgreSQL

  • Amazon RDS for PostgreSQL

  • Amazon Aurora PostgreSQL

GenAI-Driven Code Modernization

• Automated conversion of PL/SQL and T-SQL to PostgreSQL (PL/pgSQL)

• Private GenAI models trained on real-world Oracle-to-PostgreSQL and SQL Server-to-PostgreSQL migrations

• Hybrid delivery model combining AI acceleration with expert human validation

• Accelerates Oracle exit planning by replacing weeks of manual discovery with data-driven clarity.

• Provides early visibility into migration scope, risk, and remediation effort, enabling defensible business cases and executive approval.

• Reduces manual schema redesign effort and minimizes structural rework late in the project.

• Improves PostgreSQL performance alignment from day one, avoiding post-migration tuning surprises.

• Compresses code remediation timelines by up to 50%, reducing dependency on scarce specialist resources.

• Delivers up to 90% automated conversion accuracy, lowering cost while maintaining governance and control.

• Improves modernization predictability across large database estates.

Zero-Downtime Data Migration

• Continuous Change Data Capture (CDC) for live migrations

• Parallel data movement for multi-terabyte databases

• Supports phased and parallel run migration strategies

Reverse Replication & Rollback

• PostgreSQL-to-Oracle / PostgreSQL-to-SQL Server reverse synchronization

• Instant rollback capability during production cutovers

Built-In Live Data Verification

• Continuous source-to-target data validation

• Ensures migration acc

• Enables near-zero downtime cutovers, reducing operational disruption and protecting revenue-generating systems.

• Supports phased modernization strategies without forcing high-risk “big bang” migrations.

• Removes irreversible go-live risk, giving CIOs and program sponsors confidence to execute production cutovers.

• Protects business continuity with immediate fallback capability if issues arise.

• Eliminates additional tooling cost while increasing stakeholder trust in migration accuracy.

• Modernize large Oracle and SQL Server estates with clear, upfront cost visibility

• Avoid per-core or per-instance licensing models that penalize scale

• Eliminate unpredictable cloud consumption costs during long-running migrations

• Align modernization spend directly to business outcomes

Source Databases:

• Oracle

• Microsoft SQL Server

Target Platforms:

• Open-source PostgreSQL

• Amazon RDS for PostgreSQL

• Amazon Aurora PostgreSQL

• 3,500+ stored procedures, 2,000+ functions, 80+ packages

• 88% of PL/SQL auto-converted using GenAI

• Code conversion reduced from 300 person-days to under 30

• 10 TB migrated in hours using parallel processing

• Zero-downtime switchover

• Over $500K annual savings in database licensing costs

• Zero-downtime cutovers across test, staging, and production

• Hundreds of millions of records replicated within 24-hour trials

• Instant fallback enabled through reverse replication

• More than $2M annual savings

• 6,500+ T-SQL stored procedures modernized

• 85% automated schema and code conversion

• Refactoring to open-source backend and frontend technologies

• Eliminated SQL Server licensing dependency