Big-bang migrations fail because they try to replace everything simultaneously. We decompose your legacy system into modules and replace them one at a time -- each phase is self-contained, tested, and reversible. Your operation never stops. Austin is where engineering culture meets business scale. Tesla Gigafactory, Samsung's $17B chip fab, a booming tech sector, and one of the fastest-growing business markets in the country. Austin businesses demand AI systems built to engineering standards — not chatbots, not SaaS features. Custom AI agents that operate inside complex business processes, trained on your data, and owned by you permanently.
Austin businesses are tech-native and engineering-literate. They recognize the difference between an AI chatbot bolted onto a SaaS platform and a custom AI system built for their specific operation.
Break your legacy system into logical modules -- order management, inventory, pricing, financials, reporting. Define boundaries, dependencies, and migration sequence.
Prioritize which modules to migrate first based on business value, technical risk, and dependency chains. Quick wins first to build confidence.
Build integration between migrated and not-yet-migrated modules. Both systems work together during the transition period -- no functionality gaps.
Every phase has a tested rollback plan. If a migrated module doesn\'t perform, you revert to the legacy version while issues are resolved.
Defined acceptance criteria for each phase -- data accuracy, performance benchmarks, and business process verification before proceeding.
Continuous risk assessment as each phase progresses. Issues identified early are resolved before they compound in later phases.
Analyze the legacy system and decompose into migratable modules. Map dependencies between modules and external systems.
Define the migration sequence -- which module first, second, third. Build the detailed plan with timelines, resource requirements, and success criteria.
Migrate the first module with full parallel running and validation. Prove the approach works before committing to subsequent phases.
Execute subsequent phases, incorporating lessons learned. Each phase gets faster as patterns are established and integration bridges are proven.
Once all modules are migrated and validated, decommission the legacy system with data archival and compliance documentation.
Phased Migration Strategy for Austin technology & saas operations - configured around local workflows, data ownership, and implementation governance.
Phased Migration Strategy for Austin clean energy operations - configured around local workflows, data ownership, and implementation governance.
Phased Migration Strategy for Austin healthcare & life sciences operations - configured around local workflows, data ownership, and implementation governance.
Phased Migration Strategy for Austin semiconductor & electronics operations - configured around local workflows, data ownership, and implementation governance.
Phased Migration Strategy for Austin construction & development operations - configured around local workflows, data ownership, and implementation governance.
Phased Migration Strategy for Austin distribution & logistics operations - configured around local workflows, data ownership, and implementation governance.
We evaluate each module on three criteria: business value (what\'s the pain of keeping it on legacy?), technical risk (how complex is the migration?), and dependencies (what else needs to move with it?). The best first candidate is high-value, lower-risk, and loosely coupled.
We build an integration bridge -- real-time data sync between migrated and legacy modules. Orders entered in the new system appear in legacy reporting. Inventory updates in legacy are visible in the new system. Both systems stay consistent during the transition.
Typically 6-12 weeks per module depending on complexity. Simple modules (reporting, dashboards) can be faster. Complex modules (order management with custom logic) take longer. Each phase delivers a complete, usable result.
Phased migration is designed for this. Each phase is self-contained -- you can pause after any phase and the system works fine with some modules migrated and others still on legacy. Resume when you\'re ready.
ERP projects fail more often than they succeed. Not because the software is bad, but because the selection and implementation process is vendor-led instead of operations-led. Here's what good looks like before you sign anything.
Odoo covers most manufacturing operations natively. But every operation has workflows where the standard modules fall short. We map your BOMs, pricing logic, warehouse complexity, and dealer channels against Odoo's capabilities — so you go into implementation with a realistic scope, not surprises at month three.
Every failed ERP implementation has one thing in common: they migrated 20 years of bad data into a new system and expected different results. We cleanse, validate, and migrate master data with gates at every stage — so your new ERP starts with data you can trust.
Odoo doesn't run in isolation. It connects to WMS, CRM, M2B Commerce, EDI, shipping, banking, and legacy systems — all hosted and managed on AWS. Without governed integration architecture, those connections become a fragile web of point-to-point scripts that break every time something changes.
Odoo covers most manufacturing operations without a line of custom code. But when your workflows genuinely require it, we build Python custom modules — documented, tested, and upgrade-safe. We don't bolt code onto standard modules. We extend Odoo the right way.
ERP go-live is the highest-risk moment in the entire implementation. Orders are in flight, inventory is moving, and you're switching the system that governs all of it. We structure the cutover with rollback plans, validation gates, and hypercare support so your operation doesn't skip a beat.
Go-live is not the finish line — it's where the real optimization begins. Edge cases surface, users discover workarounds, and the configuration that worked in testing meets production reality. We monitor, tune, and optimize your ERP through the first 90 days and beyond so performance improves, not degrades.
The scariest moment in any migration is the cutover. We eliminate that fear by running old and new systems in parallel with automated reconciliation -- you switch over only when the new system has proven it produces the same results as the old one.
Most Odoo projects start with modules. Ours start with operational mapping. We define data contracts, integration boundaries, and go-live governance before a single module is configured.
When standard Odoo modules don't fit your manufacturing workflows, we build custom modules that extend Odoo without creating upgrade-blocking technical debt. Every custom module follows Odoo's ORM patterns and is designed to survive version upgrades.
Standard Odoo covers 80% of manufacturing needs. We close the remaining 20% with targeted customizations — module configuration, workflow adjustments, custom fields, and UI tailoring — without creating technical debt.
Odoo is rarely the only system on your floor. We integrate it with your WMS, CRM, e-commerce platform, EDI partners, shipping carriers, and legacy systems — governed by data contracts that prevent sync failures and data drift.
Metrotechs starts with the operating questions: which records are trusted, which workflows are manual, which systems own each decision, and where AI can safely improve throughput.
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