The localization stack you can't buy off the shelf.
Aurix is the AI engineering team enterprise LSPs and global content operations partner with to build their own localization infrastructure — across text, image, audio, quality systems, and the training data behind their translation models.
Trusted by enterprise LSPs
Building AI localization tools in-house is harder than it looks.
Three patterns we see in almost every language service provider trying to ship in-house — and where most builds quietly stall.
Generic devs don't speak localization.
A standard dev team will build a clean app, ask what MQM means in week three, and ship a tool linguists refuse to use. The first six weeks are onboarding tax. The next six are rework.
AI moves faster than your backlog.
A new MT engine ships every quarter. LLM capabilities shift monthly. Without a dedicated AI engineering team, your stack falls behind before the integration sprint ends.
Prototypes don't survive production.
The demo works. The pilot goes well. Then real volume hits — fifty thousand segments a day, a hundred reviewer accounts, three languages with edge cases nobody scoped. That's where most builds die.
We built the tools behind enterprise-grade AI localization.
Aurix is a specialist AI engineering team for the language industry. We're not a generic agency that takes localization projects on the side. We're the team you bring in when you've decided to build — not buy — and you need engineers who already speak the language.
Domain-Native
We know MQM scoring, MT post-edit, human-in-the-loop review, TMS integration, CAT plumbing, vendor workflows, and reviewer routing — across whatever file formats your pipeline runs on. The first call skips the 101.
AI-Driven Engineering Team
Our engineers are deeply trained in AI — LLMs, MT, OCR, computer vision, evaluation pipelines, and HITL architectures. We pick models on latency, accuracy, and cost per segment, not on slide-deck demos. AI literacy is the baseline, not a specialism.
Production-First, Not POC
Every system we ship runs daily under real load — millions of segments, hundreds of reviewer accounts, dozens of language pairs. Monitoring, observability, scale, and edge-case handling are part of the architecture, not afterthoughts.
End-to-End Ownership
Architecture through deployment through SLA. We don't hand off and disappear. You get the code, the IP, the documentation, and an engineering partner who keeps the system running and evolving.
We work with a small number of LSP clients at a time to keep quality high.
Talk to engineeringEvery layer of your localization stack.
Six categories of production AI infrastructure for language service providers — from custom translation pipelines to the data behind your own AI models.
Custom Translation Pipelines
TMS integrations, MT orchestration, LLM post-edit, and workflow automation — tailored to your pipeline, your file formats, and your vendor network. Engine routing per content type.
LQA & MQM Platforms
AI-assisted quality assessment built on MQM. Automated segment scoring, reviewer routing, dispute workflows, and dashboards that feed back into engine and supplier decisions.
Image Localization Platforms
End-to-end image localization in batches. OCR, AI text removal, contextual translation, canvas-based vendor review, structured export. Glossary-aware. Full audit trail.
Voice & Audio Pipelines
Multilingual voice data and audio translation — recording, processing, ASR, AI agents, two-pass QC, annotation. Self-hosted infrastructure so voice data never leaves your stack.
AI Training & Annotation Data
Methodology-fit annotation platforms for the data behind your AI translation models — binary, preference, summary, and domain-specific datasets. HITL loops keep data live with production drift.
Workflow Automation & HITL
Orchestration across TMS, CAT, MT, QA, and review. Connectors, job routing, quality gates, and PM controls that replace manual handoffs — so the system runs the operation.
Built for production. Trusted at scale.
Production AI localization tools running daily inside enterprise LSP and global content operations. Anonymized per NDA — full technical detail on a discovery call.
Image localization, treated as infrastructure.
Four-stage AI pipeline — OCR, inpaint, translate, render — plus a canvas review surface where vendors fix what the AI gets wrong. Multi-source ingestion. Audit-traceable on every edit.
- Multi-format export · ZIP · Drive · S3
- Vendor annotation + reviewer scoring
- Full audit trail · glossary support
MQM scoring, automated where it should be.
Dual-AI-agent detection plus a four-stage human review gate. Reviewer 1, translator, reviewer 2, arbitrator — every verdict traceable. Production scale across multiple language pairs.
- MQM-based AI scoring engine
- Human-in-the-loop override flow
- Segment-level error classification
The data behind your translation models.
A suite of annotation platforms — binary, preference, summary, ecommerce — sharing one HITL infrastructure. The model is the output. The data is the product. The annotation surface is the factory.
- Binary & preference annotation
- Summary evaluation platform
- Ecommerce domain datasets
Multilingual voice data, on owned infrastructure.
Six role-specific portals on one pipeline. Live multi-speaker recording, two AI agents, two QC passes, annotation, QA. Self-hosted WebRTC and LLM so voice data never leaves your stack.
- 9-stage pipeline · audit-grade transitions
- Two inline AI agents · eval-gated
- Self-hosted LLM + WebRTC + storage
Want technical depth + architecture diagrams?
Book a deep-dive callFrom first call to production in weeks, not quarters.
A structured engagement built for systems that ship — not pilots that stall in proof-of-concept land.
Discovery
Week 1We sit with your PMs, linguists, and ops leads. We document how work actually moves — not how the org chart says it does. Clear scope before a line of code.
Architecture
Weeks 1–2System design, data model, integration points, infrastructure plan. You approve the blueprint before we cut a line of code.
Build
Weeks 2–8+Iterative delivery with weekly demos. Working software from day one — tested against real files, real linguists, real PM scenarios. Not synthetic data.
Deploy & Maintain
OngoingProduction deployment, monitoring, ongoing iteration. We don't ship and disappear. You get an engineering partner, not a vendor handoff.
Three ways to work with Aurix
Engagement shape depends on where you are — not what we'd prefer to sell. Project build, dedicated retainer, or embedded pod.
Built with the tools enterprise demands.
Four layers, one engine. We work with your existing infrastructure or recommend the right stack. No vendor lock-in. Full code and IP transferred on delivery.
Where most agencies stop. Where we start.
Frontend
- React
- Next.js
- TypeScript
- Tailwind
- Vite
Backend
- Django REST
- Python
- PostgreSQL
- Redis
- Celery
AI / ML
- OpenAI
- Anthropic
- vLLM
- Google Vision
- MT APIs
Infra
- AWS / GCP
- Docker
- CI/CD
- Nginx
- MinIO
The engineers behind Aurix
A senior team across localization, AI/ML, and infrastructure — shipping production tools for the language industry. Everyone here is trained deeply in AI and works embedded with your workflow from week one.
Ready to build your AI localization stack?
We work with a small number of LSP clients to keep quality high. If you're evaluating a tech partner — or have a specific tool in mind — let's talk. No commitment, just 30 minutes.