Enterprise Data Platform Modernization & Migration Service

Saama provides end-to-end modernization of legacy data warehouses (Synapse, Hadoop, SQL Server, Oracle, Teradata) into cloud-native Medallion architectures, covering data, code, and validation.
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THE CHALLENGE

Breaking Free from Legacy Constraints and the Hidden Pitfalls of Lift-and-Shift Migrations.

Legacy data warehouses face rigid walls of maintenance costs and cannot support generative AI or machine learning. Basic “lift-and-shift” migrations fail by reproducing performance bottlenecks and pipeline fragility on the cloud. Critical KPI logic is often buried in undocumented stored procedures. Legacy SQL patterns (RBAR) cause failures on Spark engines, while lack of step-by-step validation risks data integrity post-cutover.

How Saama Helps

Synchronizing Enterprise Logic through a Context Graph

Saama uses AI-powered code translation and automated equivalence proofs to reset monolithic architectures into verified Medallion structures. This approach eliminates technical debt and ensures AI-ready infrastructure.

Solutions for the Modern Data Infrastructure Lifecycle

Pillar 1 — Physical Migration to Medallion Architecture

Re-baselining fragmented data into a governed, queryable foundation for enterprise intelligence.

Agents
Data Estate Re-Baseline Agent, Governance Reset Blueprint Optimizer
Medallion Alignment
Optimizing Bronze, Silver, and Gold layers for AI consumption.
Open Formats
Transitioning to Delta Lake and Apache Iceberg to replace proprietary storage.
Unified Cross-Platform Data Governance
Driven by the Governance Reset Blueprint Optimizer to replace siloed access controls with unified, platform-native governance systems using Unity Catalog or Snowflake-native boundaries.

Pillar 2 — AI-Powered Process & Code Migration

Refactoring monolithic legacy logic into distributed code blocks optimized for cloud speeds.

Agents
AI Transpilation Engine, Distributed Process Refactorer
AI Transpilation
Using AI engines to collapse manual SQL/ETL workloads from years into weeks.
Distributed Refactoring
Converting row-based PL/SQL into high-performance PySpark and dbt operations.
Business Logic Recovery & Extraction
Extracting hidden KPI calculations and compliance transformations from complex stored procedures and codifying them as version-controlled data models.

Pillar 3 — Mathematical Reconciliation & Validation

Ensuring operational success through rigorous, phase-by-phase data equivalence profiling.
Agents
Automated Equivalence Proof Engine, Lineage Continuity Sentinel
Equivalence Proofs
Continuous validation of data completeness and logical consistency throughout the lifecycle.
Per-Phase Operational Validation Gates
Forcing automated isolation boundaries to ensure data processing anomalies surface during controlled test windows before a final system cutover.
Lineage & Audit Trail Continuity:
Managed by the Lineage Continuity Sentinel to map operational metadata, historical lineage, and compliance trails across the migration boundary to protect institutional data custody.

How Saama Powers Your MDP Success

The Strategic Benefit Analysis: Enhancing the Infrastructure Lifecycle

1

Accelerated Cutover

Compress decommissioning timelines to avoid parallel licensing costs.

2

Structural Persistence

Scale long-term by transitioning to decoupled storage and compute.
3

Protected Capital

Eliminate redundant pipelines to reallocate capital to innovation.

Ready to modernize, not just migrate?

Lift-and-shift is a strategy for moving problems. We treat migration as an architectural reset – where AI-powered refactoring compresses timelines, mathematical reconciliation preserves trust, and cutover becomes a confidence event, not a survival event.