You can't integrate everything
The list of places content is created grows faster than any integration roadmap, and the ones that matter next quarter don't exist yet.
Workflow integration
You automated the request. Nobody automated the work.
Behind most translation intake, a person still reads the form and decides everything by hand, which languages, which translator, which review path. And the content that never reaches a form doesn't get decided at all.
The problem
Two kinds of invisible work
Email requests largely went away and a form replaced them. Someone fills it in, it lands somewhere, and behind it a person reads it and decides what happens, which language pairs, which translator, whether this needs review, who reviews it, what priority it gets, and what happens when it's finished.
The handoff that looks automatedWork that never reaches a form
The intake was digitised. The processing wasn't. From the outside you can't tell, because what you see is a form.
A product manager generates German copy in an internal assistant. A support agent's helpdesk auto-translates the reply. An engineer runs a JSON file through a model to unblock a build. An export manager pastes a block into a free translator, corrects it by hand and pastes it back; because raising a request takes three days and this takes four minutes.
None of that is a project. It doesn't queue, doesn't get reviewed, doesn't appear in a report. It publishes. And when the content is sensitive, it either goes into a tool it shouldn't or it doesn't get translated at all.
One kind of work looks managed and isn't. The other isn't managed at all. Neither is visible in a status report.
Why it persists
Why more connectors don't close it
Transport was never the slow part. The delay is deciding what should happen to content, and connectors only deliver it faster.
A connector moves content. It doesn't decide anything
A connector delivers content to the person who still has to decide language pairs, reviewer, priority and next steps.
It only helps content that leaves
It does nothing for anything generated and published inside the system it was born in.
The easy systems are the wrong ones
Big, central, stable platforms are easiest to connect and already most controlled. Drift lives in the long tail, tools one team adopted without telling anyone.
Research
Explore real-world translation workflow strategies
Our research analyses five enterprise case studies to show how integrated translation workflows reduce manual work, improve reuse, and support multilingual operations at scale.
What we do instead
Make the system available to the content, not the other way round
Four ways in. The same terminology, memory and style rules behind all of them.
Self-service
Three modes, depending on what the moment needs: a project, file translation with formatting intact, or an instant text box that applies approved terminology and style. The governed option becomes just as fast as the free tool.
API
Translation becomes a step in your release rather than a request that precedes it. Trigger on merge, gate on score, publish on pass.
Automation platforms
Your ops team composes the flow in the tool they already run, alongside every other integration they maintain, on their schedule, not ours.
MCP Server
Your own AI tools retrieve your language data at the moment they generate. No project, no file transfer, no login.
Routing
Nobody reads the request
Everything the person behind the form decides is a rule, not a judgement. Written once, it runs every time, including at three in the morning.
Content type and score
Routed by content type and score
A safety instruction and an internal announcement take different paths automatically.
Every segment is scored against its source, and what falls below threshold goes to a person without anyone deciding that it should.
The layer
The part that isn't a workflow
Under every other model, content travels: out of your system, into ours, back again. MCP removes the journey. Your agent asks what your company calls a component in German and gets the answer your team approved, at generation time, inside whatever tool your people already use.
Under every other model, content travels: out of your system, into ours, back again. MCP removes the journey. Your agent asks what your company calls a component in German and gets the answer your team approved; at generation time, inside whatever tool your people already use.
TextUnited stops being a destination that work goes to and becomes a dependency that other systems consult. That's the difference between integrating a translation tool and having a language layer.
MCP deployments are configured per organisation as part of an enterprise engagement.
Scope
Centralisation without a queue
One language layer, many consumers. The documentation pipeline, the support tool, the marketing team's assistant and the release process all read the same terminology and the same approved history; without any of them routing through a central project queue.
What gets centralized is the language data. The workflows stay where they are.
Getting started
Four ways in. Two of them you can start today.
Self-service and the API are available on sign-up, translate a file, try the terminology-aware text box, or put a call in your pipeline this afternoon. Automation platform builds and MCP deployments are designed with you.
Business outcomes
Make the governed path the fast one
A governed path works when it is as fast and useful as the unsanctioned alternative.
Governed becomes the fast option
People use free tools because they're instant. An instant tool that applies your terminology removes the reason to go elsewhere.
Sensitive content stops leaving
A sanctioned path as quick as the unsanctioned one is the only version of this policy that holds.
Consistency without coordination
Every surface reads the same terminology, so alignment doesn't depend on everyone remembering the same thing.
Integrations you own
Built against the API or in your automation platform, maintained on your schedule rather than a vendor's roadmap.
Scale by adding consumers
New teams and tools read from the layer instead of joining a queue.
Decisions stop waiting on people
Routing, review path and downstream steps run as rules, so work moves overnight and across time zones.
Use cases
Built for teams with recurring multilingual content
Recurring content benefits most when translation becomes part of the systems that create and publish it.
Software teams
Translation as a pipeline step, so strings keep pace with releases.
Product teams
Product content, UI strings and release notes aligned across markets.
Technical documentation
Approved terminology reused across recurring updates.
Marketing
Campaign content localised without email handoffs, with an instant option for small things.
Legal
Controlled, reviewable workflows for contracts, policies and regulated content.
Localization teams
Language assets, reviewers and delivery coordinated in one place.
Get started
Put the language rules where the content is being made
Connect the systems you want, and make the terminology available to the ones you never will.
FAQ
Questions about translation workflow integration
Answers about integrations, automation, security and scaling multilingual workflows.
What systems can TextUnited integrate with?
Anything that can make an HTTP call, which in practice is everything. Integrations are built against our API or composed in an automation platform your team already runs.
Can we keep our existing systems?
That's the assumption. Nothing needs replacing or migrating, content stays where it's created and published, while terminology and approved history become available to it.
What does localization workflow automation actually include?
More than moving files: content entering from wherever it's created; automatic routing by language pair, content type and quality score; review assigned by rule; and steps after delivery such as updating the system of record, notifying the market owner and publishing.
Do we need a developer?
For the API, yes, briefly. For self-service, projects, file translation and the instant text box, no. Automation platform builds sit in between.
Is our translation data secure?
Your language assets sit in your own tenant and aren't used to train public models. A governed option that's equally fast helps prevent sensitive content going into free public tools.
Does TextUnited support AI and human workflows together?
Yes. Every segment is scored against its source; what falls below the threshold goes to a person, and what clears it continues.
Can the workflow scale across teams and languages?
Adding a team means giving another system access to the layer, not adding another queue. Users are unlimited from OnePlatform upward, so scaling access isn't a licensing decision.