Migrations & Upgrades

We use AI assistants as technical partners to diagnose issues faster and generate solutions more accurately. Every output is reviewed and tested before deployment.

AI accelerates critical work in two ways: First, it helps us pattern-match against thousands of known scenarios, narrowing diagnosis time from hours to minutes. Second, it generates code that we verify against your specific tech stack. You're paying for expertise in using AI well—knowing when to trust it, when to override it, and how to test thoroughly.

Think of it like an experienced mechanic using diagnostic software. The tool speeds things up, but the human expertise determines the actual solution.

Yes. We use external AI providers (like OpenAI, Anthropic) with strict privacy modes enabled. Your code is processed but never used to retrain their models and is not retrievable by anyone else.

Here's how we protect your information: All major AI providers offer enterprise privacy settings that prevent your data from being stored long-term or used for model improvement. We work exclusively with these privacy-enabled modes. For sensitive data (API keys, credentials, personal information), we sanitize or exclude it entirely before any AI processing. We also sign NDAs for confidential projects.

For authentication systems, payment handlers, and personal data processing, we often write critical sections manually with zero AI involvement. Security isn't negotiable—we balance AI efficiency with your privacy requirements.

We review every line of AI-generated code before it reaches production. No AI output goes live without human verification, testing, and security review.

Our workflow: AI suggests solutions, we evaluate them against your requirements, test for edge cases, check for security vulnerabilities, and verify the code integrates properly with your existing system. We treat AI suggestions like junior developer output—useful starting points that require experienced oversight.

What we check: Security flaws (SQL injection, XSS, authentication bypasses), performance issues (N+1 queries, memory leaks), maintainability (is this code readable in 6 months?), and business logic correctness (does it actually solve your problem?). Insecure or poorly architected code gets rewritten or rejected, regardless of whether AI or humans wrote it first. You're protected by our review process, not blind trust in AI output.

We're transparent about this: AI tools are integrated into our development workflow, and we believe that benefits you directly. Modern development assistants help us write cleaner code faster, catch bugs earlier, and maintain consistency across your project — which means better quality at fair prices.

But here's what matters: Your project data, business logic, and sensitive information stay private. We use AI the same way we use any professional tool — strategically, with full control over what gets processed and how. Think of it like spell-check for code, not outsourcing your project to a black box.

If you have specific privacy requirements (healthcare data, proprietary algorithms, regulated industries), we work within those constraints. We can discuss exactly what tools are used where and adjust our approach for sensitive components.

What we won't do is pretend the industry hasn't evolved. AI-assisted development is now standard practice at serious software houses — the difference is whether your provider is honest about it and uses it responsibly. We are, and we do.

We create complete backups before touching anything, test the migration in a staging environment first, and verify data integrity before switching production. Data loss is preventable with proper process.

Our migration safety protocol: Full database backup before migration (stored offsite, not just on the same server), complete file system backup (media uploads, configurations, everything), staging environment testing (we run the full migration on a copy of your live site first), data validation (comparing record counts, spot-checking critical data, testing user logins and content), and rollback plan (documented steps to revert if something goes catastrophically wrong).

Where data loss typically happens in botched migrations: Skipping backups (amateur hour), migrating production directly without staging tests (reckless), assuming automated tools work perfectly (they don't), and ignoring data type conversions (dates, currency, text encoding all cause subtle corruption). We've rescued projects where previous developers lost data during migration. It's always the same failures: rushing, skipping staging tests, no backups, or blind trust in migration scripts. We don't make those mistakes. If we say your data is safe, it's because we've proven it safe in staging before touching production.

Depends on database size and complexity. Small sites: 1-4 hours. Medium sites: 4-12 hours (usually overnight). Large sites: 12-24 hours or phased migration with minimal user-facing downtime.

Downtime factors: Database size (migrating 100MB takes minutes; 50GB takes hours), data transformation complexity (simple copy-paste vs. complex restructuring), DNS propagation (if changing hosting, this adds 1-24 hours regardless of technical work), testing and verification (we don't flip production live until thoroughly tested), and your acceptable risk tolerance (faster migration = less testing = higher risk of issues post-launch).

Minimizing downtime: We schedule migrations during your lowest-traffic windows (typically 2-6 AM local time), prepare everything in advance (staging migration completed, all issues resolved, production steps documented), and use techniques like database replication (for very large databases) or phased rollouts (migrating sections gradually instead of all-at-once). For high-traffic sites where downtime is costly, we can implement more complex strategies (blue-green deployment, gradual traffic shifting), but these add cost and complexity. Most small-to-medium migrations happen overnight with a maintenance page—users wake up to the upgraded system without noticing the transition.

Rarely. "Impossible" usually means "difficult" or "I don't know how." Most systems can be migrated with enough technical effort, though sometimes rebuilding is more cost-effective than migrating.

Why developers claim "impossible": Unfamiliarity with the target platform (they know WordPress, not Laravel), custom code tightly coupled to old framework (poorly architected from the start), proprietary data formats with no export tools (but databases are still accessible), or honest assessment that migration cost exceeds rebuild cost (sometimes this is accurate).

What's actually impossible vs. just difficult: Impossible—migrating when source system is completely lost (no database access, no backups, no code). Difficult but doable—migrating from proprietary platforms, extracting data from poorly structured databases, converting complex custom features to new platform, preserving URL structure when platforms handle routing differently. We assess these situations honestly: Sometimes migration is technically possible but economically stupid. If rebuilding costs €5k and migration costs €15k due to complexity, we'll recommend rebuilding. But if your developer said "impossible" without even attempting assessment or offering alternatives, they either lacked expertise or didn't want to deal with complexity. Get a second opinion—ours is free during initial assessment.

We roll back to the pre-migration backup, investigate what failed, fix the issue in staging, and retry. This is why we never migrate without tested backups and rollback procedures.

Rollback scenarios: Database migration corrupted (restore database backup, typically 15-30 minutes), application code broken post-migration (revert code, restore backups), DNS/hosting issues preventing site access (revert DNS changes), or partial migration succeeded but critical features broken (rollback entirely, fix issues, retry later). Having a documented rollback plan means failures are recoverable, not catastrophic.

Common migration failures we prepare for: Plugin/extension incompatibilities discovered post-migration, performance issues from inefficient queries on new platform, third-party integrations breaking due to API version changes, edge-case bugs not caught during staging tests (obscure user workflows, specific data combinations), and caching issues causing stale content or broken functionality. When failures occur: We communicate immediately (not hide problems), execute rollback if necessary (back online quickly, even if not migrated), diagnose root cause, fix in staging, and retry when ready. What separates professional migrations from disasters: We expect problems and plan for them. Amateur migrations assume everything will work perfectly—then panic when it doesn't.

Usually, yes. If we can access the database and understand the data structure, migration is feasible. Custom systems are harder than standard platforms, but not impossible.

Custom system migration challenges: No documentation (we reverse-engineer database schema and business logic), proprietary data formats (requires custom extraction scripts), tightly coupled code (features built specifically for old platform need rebuilding), and unknown dependencies (undocumented integrations that break post-migration). These add time and cost but don't prevent migration.

Our approach: Database analysis (mapping tables, relationships, data types), data extraction (writing scripts to export everything in usable formats), data transformation (converting proprietary structures to standard formats), feature inventory (identifying what needs rebuilding vs. what maps directly), and phased migration (moving core functionality first, then advanced features). We've migrated from ancient ASP.NET systems, custom PHP frameworks from 2005, Access databases, and even Excel-based "systems" (yes, really). If the data exists and is accessible, we can migrate it. The question is cost vs. benefit: Sometimes custom systems are so convoluted that rebuilding with modern tools costs less than untangling the old system. We assess this during discovery and give you honest recommendations.

Not if handled properly. We implement 301 redirects for all URL changes, preserve meta tags and content, and maintain site structure. Google treats proper migrations as site improvements, not penalties.

SEO preservation checklist: URL mapping (old URLs redirect to equivalent new URLs via 301 permanent redirects), meta data migration (page titles, descriptions, Open Graph tags), structured data preservation (JSON-LD schema markup), XML sitemap generation (submit new sitemap to Google Search Console immediately), internal linking structure (maintaining navigation and cross-links), and page speed optimization (new platform often faster, which helps SEO).

Where SEO gets destroyed during migrations: Broken URLs with no redirects (404 errors tank rankings), changed URL structure without mapping old to new, lost meta descriptions and title tags, removing content during "cleanup", slow new platform (page speed is ranking factor), and mobile responsiveness issues (mobile-first indexing is default now). We monitor these carefully. Expect minor ranking fluctuations during migration week—totally normal as Google reindexes. But within 2-4 weeks, rankings typically stabilize or improve (modern platforms are usually faster and better structured). If rankings tank significantly, it's fixable with proper redirects and technical SEO adjustments. We provide post-migration monitoring and fix any SEO issues that emerge during the transition period.