Your organization uses Phrase. Or Lokalise. Or MemoQ. Or one of dozens of other translation management systems. The workflows are established, teams are trained, data lives there.

Now you need a capability your TMS doesn’t have—advanced AI translation, cross-lingual QA, video dubbing. Do you switch platforms?

Switching is painful. Connectors offer an alternative.

The platform switch problem

Changing TMS platforms involves:

Data migration. Translation memories, termbases, project history—all needs extraction and import. TM quality often degrades in translation between formats.

Workflow disruption. Existing processes stop working. New processes need design and documentation.

Team retraining. Everyone who touches translation needs to learn new tools.

Integration rebuilding. Any integrations with other systems (CMS, repositories, ticketing) need reconnection.

Vendor coordination. External translators and agencies need to adopt new systems.

Transition period chaos. During migration, some projects are in the old system, some in the new. Coordination nightmare.

All of this for capabilities that could be added without replacing the core system.

The connector model

Connectors extend your TMS rather than replacing it:

Your TMS remains the system of record. Projects, TMs, terminology, workflows—all stay where they are.

Connected platform provides additional capabilities. Whatever your TMS lacks—advanced AI, specialized QA, video processing—plugs in via integration.

Content flows between systems. Projects export from TMS, process through connected platform, return to TMS with enhanced content.

Teams work in familiar environments. The TMS interface doesn’t change. Additional capabilities are accessed when needed.

What connectors enable

Capabilities commonly added through connectors:

AI translation enhancement. Your TMS may have basic MT. A connector adds frontier AI models, council translation, and AI enhancement pipelines—with local model options for data privacy.

Cross-lingual quality assurance. Run QA checks that your TMS doesn’t offer—LLM-based evaluation, dual-model scoring, advanced rule sets.

Video and audio processing. Transcription, translation, dubbing for multimedia content that most TMS platforms don’t handle.

Advanced file processing. AI-powered extraction, format detection, and handling for file types your TMS struggles with.

Content discovery and transcreation. Market research and creative adaptation tools that complement translation workflows.

The connector adds what’s missing; the TMS handles what it does well.

How connector integration works

Typical connector architecture:

Project sync. Create or import projects from TMS. Language pairs, settings, and source content transfer.

Content transfer. Source files and/or XLIFF exports move to the connected platform for processing.

Processing. AI translation, QA, video processing, or whatever capability is needed.

Return transfer. Processed content returns to TMS—translated files, XLIFF with translations, QA reports.

TM update. Final approved translations update the TMS translation memory.

The flow can be automated (every project processes through connector) or selective (specific projects use connector capabilities).

Credential and security handling

Connector platforms need access to your TMS. Security considerations:

API credentials. TMS access requires API keys. These should be encrypted at rest and in transit.

Data handling. Content passing through connectors should be protected appropriately. Understand where data is processed and stored.

Access control. Connector access should be limited to necessary permissions. Not everyone needs to configure integrations.

Audit logging. Track what content flows between systems and what actions connectors take.

Evaluate connector security before granting TMS access.

Connector vs. replacement decision

Sometimes connectors are the right choice. Sometimes platform replacement is better.

Connectors work best when:

• You need specific capabilities your TMS lacks
• Your TMS does most things well
• Migration cost exceeds capability gap cost
• Workflow disruption is unacceptable
• You want to evaluate capabilities before committing

Replacement may be better when:

• Your TMS has fundamental limitations across many areas
• Integration overhead exceeds benefit
• You’re already planning a system change
• Connector costs approach replacement costs
• Unified workflow matters more than capability access

The decision depends on your specific situation—neither is universally correct.

Available connector patterns

Different TMS platforms offer different integration possibilities:

API-based connectors. For platforms with robust APIs (Phrase, Lokalise, Crowdin), connectors interact programmatically. Most flexible option.

XLIFF exchange. For platforms with limited APIs, XLIFF export/import provides a universal exchange format. Works with any TMS that supports XLIFF.

Webhook integration. Platforms that support webhooks can trigger connector processing automatically on project events.

Manual handoff. Simplest pattern—export from TMS, upload to connector platform, download results, import to TMS. More work but works with any system.

The available patterns determine how seamless the connector experience can be.

Multi-connector architectures

Organizations may use multiple connectors for different capabilities:

• TMS → AI translation connector → back to TMS
• TMS → Video processing connector → back to TMS
• TMS → QA platform → back to TMS

These can chain or run in parallel depending on workflow needs. The TMS remains central; connectors provide specialized processing.

The gradual enhancement path

Connectors enable gradual capability building:

Phase 1: Connect AI translation for high-value projects Phase 2: Add QA automation for all projects Phase 3: Integrate video processing as needs grow Phase 4: Evaluate whether full platform migration makes sense

Each phase adds value without disrupting what’s working. The organization learns what capabilities matter before committing to architectural changes.

Evaluating connector options

When evaluating connector solutions:

Integration depth. How tightly does it connect with your TMS? Automated or manual sync?

Capability coverage. Does it provide the specific capabilities you need?

Security posture. How does it handle your data? Where is content processed?

Cost structure. Per-word, subscription, or project-based pricing?

Support availability. When integration issues arise, who helps resolve them?

Pilot connectors on limited projects before broad deployment to verify they work as expected in your environment.

Language Ops provides connectors for Phrase, Lokalise, Crowdin, and other major TMS platforms, adding AI translation, cross-lingual QA, and video processing to your existing workflows. Connect your TMS to explore available capabilities.