Keep your engineers on your product, not your translation stack.
Ship in every language as fast as you ship in one. Phrase gives your teams the platform to generate, govern, and release global content at scale, so your best engineers stay on the product only you can build.
Translation is the easy part now
Modern models are good. You can send content to an LLM and get fluent translations back in minutes, and a capable team can stand that up quickly. That’s real progress, and it’s worth using.
The interesting work starts at volume. Staying accurate, on-brand, compliant, and consistent across every language and every release is a different kind of problem, and it’s the one that was always hard. AI scaled the translation step. The system around it still has to be built and run.
The platform your product builds on
Everything that keeps global content correct at scale is real engineering. Routing across models and engines per language. Measuring quality automatically as models change. Keeping terminology and brand voice consistent. Connecting every system where content is created and shipped. Staying compliant and auditable throughout.
That’s a platform. You can build and run it yourself, or you can build on one that already exists. Phrase is that foundation, so the layer beneath your product is something you configure and control rather than something you maintain forever.
For business leaders:
What building this in-house really involves, and what buying instead frees up.
For engineering leaders:
What production asks of a global-content system, and the platform primitives that carry it.
For business leaders
Building a global content stack in-house is less a project than a product, and products need permanent teams. The line you approve at the start tends to be smaller than the one you live with, so it’s worth seeing the whole commitment before you take it on.
A standing team
The stack needs ML ops, data engineering, QA, compliance, connector maintenance, DevOps, and linguists. It’s a roster you fund every year.
Connector upkeep
Every CMS, DAM, help desk, design tool, or vendor API that changes becomes your team’s to fix, test, and monitor.
Time to safe scale
Governance and quality layers aren’t optional, and they take months to build well. That’s time before you can ship confidently in every market.
Where your engineers go
Your scarcest resource is engineering time. Spent on plumbing, it’s spent on something a competitor can also buy.
Treat global content as an enterprise asset.
The model that scales is central governance with distributed execution: local teams move fast while global guardrails hold. Product, UX, engineering, and content all touch multilingual content, and a single governed platform makes that content predictable across all of them.
Phrase recognized as a Leader in the Forrester Wave™, Q3 2025
We scored top marks in 21 of 26 criteria, setting the benchmark for enterprise language technology.
For engineering leaders
Most engineering teams can prototype LLM-based localization in a sprint, and the prototypes are convincing. Production is where the interesting engineering lives, and it has little to do with the model. It’s systems design: versioned content, translation memory hygiene, prompt management, quality evaluation, compliance, and orchestration. Inference throughput scales easily. Nuance is the part that needs infrastructure.
What production asks of you:
Consistent quality
Automated detection and regression tracking keep quality steady as models change, not drifting quietly at volume.
Terminology and tone
Fluent isn’t accurate. Enforced termbases and brand voice keep output consistent across languages.
Real context
Context spans UI state, history, audience, brand, and regulation, modelled as typed metadata, solved as retrieval.
Reproducibility
Model updates shift output. Versioned prompts and rollback keep behavior governed.
Data governance
Custom models need provenance tracking and compliance monitoring to keep legal risk in check.
The honest scope of building it
Taken together, that’s an internal platform to own and run, and it’s the reason a specialist platform exists.
Technical
Prompt ops, context engineering, TM sync, multimodal fidelity, observability, large-file ingestion, and CI/CD coordination.
Operational
Workflow orchestration, quality evaluation, multi-engine routing, technical debt, and integration upkeep.
Data and compliance
Residency, encryption, certification (GDPR and industry-specific), model governance and provenance.
Organizational
Long-term staffing, cross-functional alignment, and the engineering focus it pulls from your core product.
What good looks like
The teams that get the most from this treat localization as long-term infrastructure rather than an experiment. They put their engineering effort into how it fits their CI/CD, release, and quality workflows, and let the platform handle the repeatable concerns: orchestration, governance, connectors, and observability. Engineering time compounds when it’s spent on what differentiates the product.
Build with the Phrase platform
Developer-first integration
Robust APIs, SDKs, and 200+ prebuilt connectors to CMS, design, and code systems.
Modular and extensible
Plug-in connectors, configurable workflows, and governance templates let each team adapt behaviour while central control holds.
Workflow orchestration
A visual orchestration engine models triggers, conditional logic, quality gates, and human-in-the-loop review, so you’re building on a workflow layer rather than maintaining glue code.
Governed AI
ML-driven routing (MT Autoselect), custom AI training, automated LQA, and quality analytics, improving quality and throughput without sacrificing transparency, ownership, or compliance.
Orchestrator
A configurable hub for model configuration, routing, templates, and integrations that teams tailor to UI, marketing, support, and release workflows.
Security and compliance
Enterprise-grade encryption, role-based access, audit logging, and regional hosting that meet common certification needs.
Build with Phrase
Ask whether building this makes you more competitive than buying it. If the answer isn’t a clear yes, build on the platform and point your engineers where they move the needle.
Prototype success isn’t the same as production readiness. The hard part of global content at scale was never the translation. It’s the system engineering that keeps context, quality, and governance intact across content types, languages, and markets.
Build what differentiates you, and create the rest on Phrase.
FAQs
Isn’t an LLM API enough now that models are this good?
The model is the easy part. Keeping output accurate, consistent, compliant, and reproducible across languages and releases takes routing, quality evaluation, terminology, context, and rollback. That work exists whether you build it or buy it, and Phrase is where it already lives.
How does the cost of Phrase compare to building in-house?
Building in-house isn’t a one-time cost, it’s a standing team and ongoing maintenance you fund every year, plus the engineering time it pulls off your product. Total cost of ownership almost always runs higher than a platform subscription, and it keeps growing as you add markets and languages.
How is Phrase different from calling an LLM ourselves?
Phrase governs the model rather than only calling it: versioned prompts, automated quality checks, model routing, translation memory, audit trails, and rollback. You get the LLM’s speed with the controls a production system needs.
Do we keep control and data ownership on a platform?
Yes. Custom AI training pipelines, data residency options, role-based access, and audit logging keep data ownership and governance with you.
Can our engineers still customise it?
Yes. APIs, SDKs, 200+ connectors, configurable workflows, and the Orchestrator are built for teams to adapt Phrase to their own systems and cadences while central governance holds.
What does it integrate with?
CMS, DAM, code repositories, design tools, help desks, and release pipelines, through 200+ prebuilt connectors, plus the API for anything bespoke.
How fast can we get to production?
Prebuilt connectors and workflows turn what would be months of infrastructure work into weeks. Your team spends that time on how global content fits your product.