Phrase Forward Deployed Engineering
Phrase engineers embed with your team to ship AI translation pipelines into your stack. Fixed scope, fixed fee, one calendar month.
Forward Deployed Engineering, built around language
Forward Deployed Engineering is the model that enterprise AI is increasingly shipped through: senior engineers embedded with the customer’s team, building production systems directly into the customer’s stack.
Phrase FDEs are the team for language operations. Our engineers arrive with the Language Intelligence Platform already handling context, evaluation, routing, and governance. They configure it, extend it, and connect it into your environment. That’s why a Phrase FDE engagement ships in weeks and why the result holds up in production where generalist AI deployments often don’t.
Production AI is an engineering problem
You’ve got AI on the roadmap. You may already have a pilot running. The hard part is what comes next: getting AI into production at quality, on integration, with governance, and without breaking the workflows your business already depends on. That’s ‘engineering work’. It’s the bottleneck that has stalled most enterprise AI in language operations.
Internal teams are stretched
Your engineers have a roadmap. Your data team has a backlog. AI in production has to wait its turn.
AI quality is inconsistent
The same prompt can return different results. Without rigorous evaluation, nobody’s willing to put it in front of customers.
Legacy content isn’t AI-ready
The content you want to translate lives in formats and structures your AI can’t use yet.
We build the pipeline. You run the business.
Traditional services teams give you a plan. Phrase Forward Deployed Engineers give you a running system.
Our FDEs are senior engineers bringing deep language domain and AI deployment expertise directly to your team. We write production code and deploy AI pipelines in your environment, and stay until your system is quality-validated and handed over.
Fixed-scope, fixed-fee, and outcome-defined.
| Traditional professional services | Phrase Forward Deployed Engineering |
|---|---|
| Delivers a plan and recommendations | Delivers a running system in production |
| Day rates, variable costs, open scope | Fixed price, fixed scope, defined outcome |
| Knowledge transfer through training | Knowledge transfer through runbooks and a live pipeline |
| Your team carries the build risk | Our experts own execution until full handover |
What the full handover looks like
A live AI translation pipeline
Deployed in your environment. Quality-validated. Running independently from day one of handover.
AI quality routing
Built on Phrase Quality Performance Score. Content routes through the right path – machine, post-edit, or full human – based on signals you can audit.
Data and integration foundations
ETL pipelines, content restructuring, integration health audits, and the architecture decisions that make your stack AI-ready beyond the engagement.
Quality evaluation that holds up
Automated evaluation rounds plus a human review layer. The pipeline goes live because it passed, not simply because the timeline ran out.
Fixed scope. Fixed fee. Weeks, not quarters.
Phrase 1: Discovery (around 5 days)
We define the outcome you’re buying – cost, quality, or speed – map your integration architecture, audit your data, and align on scope. If Discovery surfaces a misfit, we adjust before committing to execution. You’re never locked in to building the wrong thing.
Phrase 2: Execution (around 8 to 25 days)
The FDE plus Project Manager pod deploys to your environment. Data cleaning, workflow design, prompt engineering, and up to three automated evaluation rounds. The pipeline is built, tuned, and stress-tested in your stack.
Phrase 3: Handover
(around 3 to 7 days)
A quality-validated pipeline in production, runbooks, best-practice documentation, and a knowledge-transfer session with your engineering team. The pipeline runs independently once handover’s signed.
Three ways to engage.
One fixed fee on every engagement.
Use case deployment
A focused engagement for a single AI use case across a small set of languages. Two automated evaluation rounds and one round of fixes.
Best for teams putting a defined AI use case into production before scaling.
Business AI deployment (Recommended)
A broader build covering two to three AI use cases across more languages. Full Discovery, execution, three automated evaluation rounds, and complete handover.
Best for strategic accounts deploying AI across multiple content streams.
Enterprise/bespoke
Custom-scoped, multi-content, multi-language deployments. Right-sized to your business case.
Best for global organisations putting AI into production at scale.
Every engagement is fixed-scope and fixed-fee, defined in the SOW, with a quality-validated handover. Talk to us for a scoped proposal.
Outcomes we’ve delivered
CUSTOMER STORY
Full automation
Enterprise Software (SaaS)
For the same customer’s product pages across 22 locales, every translation got a human pass after machine translation, a slow habit at that volume. An FDE deployed Auto Adapt across all 22 locales and tuned it twice for brand voice and tone, replacing human post-editing entirely. Delivery on this content stream dropped from about a month to 1-2 business days.
CUSTOMER STORY
Adaptive Quality
Healthcare
Sensitive health content across 7+ languages needed surgical precision. Terminology, tone, and compliance all had to hold up, with no automated way to catch a miss before it shipped. An FDE built a self-improving AI orchestrator that runs multiple quality checks and feeds the results into a learnings database. Human review is down by roughly 50%, and the pipeline keeps getting sharper on its own.
FAQs
How is Phrase FDE different from a generalist Forward Deployed Engineering team?
Generalist FDE teams build AI applications from scratch. Phrase FDEs configure and extend the Language Intelligence Platform – which already handles context, evaluation, routing, and governance for language operations – into your stack. That makes the engagement faster, more predictable, and more cost-effective for any team whose AI use case touches language.
We have our own engineering team. Why do we need this?
Your team has a roadmap and a backlog. FDEs accelerate, they don’t replace. The engagement compresses what would otherwise be a multi-quarter internal build into roughly a month, with your team focused on the parts only your team can do.
How is this different from professional services?
Traditional services delivers a plan, a recommendation, or a configured product. FDE delivers a running system in your environment, with code written into your stack and a pipeline quality-validated to production standard. The engagement is fixed-scope and outcome-defined, rather than day-rate.
AI translation quality isn’t always reliable. How do you handle that?
Every engagement includes structured quality evaluation – automated evaluation rounds plus a human review layer, scaled to the package. The pipeline goes live because it passed, not because the deadline arrived. The technical risk of the build sits with Phrase during the engagement.
What happens after the engagement ends?
You own a running pipeline in production, full documentation, runbooks, and a knowledge-transfer session with your engineering team. The system’s built to run independently. Ongoing platform support continues through your standard Phrase account team.
How quickly can we start?
Discovery typically begins within two weeks of contract signature. Most engagements complete inside a single calendar month from Discovery kickoff.
Who owns the pipeline at the end?
You do. The deployed pipeline, the integration code, and the documentation are yours.
Let’s get your AI into production
Talk to Phrase about a fixed-scope, fixed-fee Forward Deployed Engineering engagement that puts AI to work in your stack.