Modernize Your Data. Move to the Cloud. Without the Risk
We run migrations for organizations that cannot afford downtime, data loss, or surprises. Fixed scope, validated outcomes, and a handover your team can operate.
Modernizing a Data Estate Is a Business Continuity Problem
Legacy platforms carry hidden cost
Aging databases, warehouses, and batch jobs consume budget in maintenance, licenses, and operational risk.
- License and maintenance drag
- Operational fragility
- Slow change cycles
Data trust breaks before analytics does
Siloed schemas, duplicate sources, and manual reconciliations make teams hesitate before using the numbers.
- Fragmented schemas
- Manual reconciliation
- Duplicate sources
AI needs a modern data foundation
Reliable AI and analytics depend on scalable storage, governed pipelines, and access patterns designed for production.
- Governed pipelines
- Scalable storage
- Production-ready access
Modernization, not just migration
We help define the target platform, move the critical workloads, and validate that the new estate is ready for operations.
Database migration
Move SQL Server, PostgreSQL, MySQL, Oracle, and MongoDB workloads to managed cloud platforms with integrity checks and cutover planning.
Warehouse modernization
Re-platform legacy warehouses to Snowflake, BigQuery, Databricks, Redshift, or cloud-native database services with performance in mind.
Pipeline modernization
Replace brittle batch jobs with managed pipelines, streaming patterns, orchestration, monitoring, and clear data ownership.
Platform strategy
Design the governance, cost model, security posture, and migration roadmap before teams commit to a target architecture.
Fixed Scope. Fixed Price. No Surprises
Assess and map
We inventory the estate, map dependencies, identify risk, and define the cutover path before migration begins.
Deliverable: modernization roadmap with dependency map, risk matrix, target-state recommendation, and fixed-scope proposal.
Pilot and validate
We move a controlled workload first, validate schema compatibility, reconcile data, and rehearse rollback before production cutover.
Deliverable: validated pilot environment with reconciliation notes, performance observations, and rollback procedure.
Migrate and cut over
We execute the migration with runbooks, monitoring, reconciliation, and a tested rollback plan in place.
Deliverable: production-ready platform with validated data, architecture notes, and operational runbook.
Optimize and hand over
We tune cost and performance, document the operating model, and transfer knowledge so the platform is not a black box.
Deliverable: optimization backlog, runbook, architecture diagram, and handover session for your team.
We recommend the platform that fits.
We are not a cloud reseller. The target architecture should match your stack, team skills, compliance needs, latency constraints, and operating budget.
AWS | Azure | Google Cloud | Snowflake | Databricks | MongoDB Atlas | Confluent | dbt
Relational systems
SQL Server, PostgreSQL, MySQL, Oracle, managed database platforms, and cloud-native migration patterns.
Analytical platforms
Warehouse, lakehouse, streaming, orchestration, semantic layers, and governed analytics foundations.
Not sure how ready your data estate is for AI? Take the readiness assessment
What done looks like
The goal is not just to move data. The goal is a platform that is validated, observable, and ready for the next wave of analytics and AI.
Planned cutover
Migration windows, rollback plans, monitoring, and stakeholder checkpoints are defined before production moves.
Data integrity validation
Reconciliation checks, row counts, schema reviews, and acceptance criteria make trust measurable.
Fixed-scope delivery
Each phase has a decision gate, expected deliverables, and a clear path to continue or stop.
Cost-aware architecture
Storage, compute, indexing, retention, and workload patterns are designed before cloud costs drift.
Team-owned operations
Your team receives the runbook, architecture diagram, operating notes, and handover needed to run the platform.
AI-ready foundation
Governed, reliable data pipelines make analytics, automation, and AI delivery safer to scale.
Built by architects and engineers who have migrated data at enterprise scale
The same architects and engineers leading your engagement have delivered cloud transformations across aviation, energy, and fintech in heavily regulated environments where downtime is not an option.
Select Client Outcomes
Production migrations led
Years enterprise architecture experience
Regulated industries
Unplanned downtime in mission-critical cutovers
Let's build something
