Your AI translates the language.ACROSS translates your company.
Generic models have never read your glossary, your translation memory or your style guide. ACROSS turns that buried knowledge into a multi-agent pipeline — so your team certifies output instead of rewriting it line by line.
Drops into your existing CAT tool — no workflow rewrite.
across · review workspace — EN → ES
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Envía tu informe de gastos antes del cierre del período.
Your workspace admin can reset multi-factor authentication.
El administrador del espacio puede restablecer la verificación en dos pasos.
Effective 15-JUN-2025, the new policy applies to all regions.
A partir del 15 de junio de 2025, la nueva política se aplica a todas las regiones.
312 segments · 87% auto-approved
The gap
AI knows the language. It doesn't know your company.
Post-editing exists because people manually re-apply knowledge the company already owns. That's not a translation problem — it's a context delivery problem.
What the model gets today
- Raw source text
- A generic instruction
- Public internet knowledge
- Almost no business context
What correct output actually needs
- Translation memories
- Approved glossaries
- Style & tone guides
- QA & do-not-translate rules
The knowledge isn't missing. It's just never reaching the model.
The product
One harness. Four agents. Your knowledge in the loop.
ACROSS sits between your content and your reviewers, orchestrating specialised agents that each enforce a different part of your standards.
1 · Your knowledge
- Translation memories.TMX
- Approved glossaries.TBX
- Style & tone guidesPDF / DOCX
- QA & do-not-translate rulesPrivate profile
2 · Multi-agent orchestration
Translation
Drafts against your TM, not a generic corpus.
Post-editing
Applies brand voice and tone rules automatically.
Terminology
Enforces approved terms, flags forbidden ones.
QA
Catches omissions, format and compliance breaks.
Ingestion · Retrieval · Playbooks · Evaluations
3 · Human validation
- Accept
- Edit
- Reject
Every decision is captured as a structured correction signal and fed back into the system.
>50%
less post-editing effort
at strict quality parity
87%
segments auto-approved
after 3 feedback cycles
4
specialised agents
working in one pass
100%
human-validated output
on regulated content
Target outcomes based on pilot design criteria. Figures shown are illustrative.
Compounding advantage
Every correction makes the next batch better.
Most tools forget what your reviewers just fixed. ACROSS turns each decision into training context for the next run.
01
Ingest
TMs, glossaries and style guides become structured context.
02
Generate
Agents draft, post-edit and validate in a single pass.
03
Validate
Your reviewer accepts, edits or rejects.
04
Capture
Every correction becomes a structured signal.
05
Improve
Retrieval and playbooks update themselves.
What teams say
Reviewers stop rewriting. They start certifying.
“Our style guide used to live in a PDF nobody opened. Now it's enforced on every single segment, automatically.”
“Reviewers stopped rewriting the same five terminology mistakes. They finally review meaning instead of fixing vocabulary.”
“We plugged it in as an MT provider inside our existing CAT tool. Zero workflow disruption, measurable drop in edit distance.”
Sample quotes shown for illustration.
The team
Localisation research meets production AI engineering.
Vicent Briva-Iglesias
- Assistant Professor at DCU, Chair of MTS and MTT and member of the AI in Education Advisory Group
- Adjunct Professor in Language Technologies at McGill University and Universitat Oberta de Catalunya
- External researcher of AI for healthcare at the Barcelona Supercomputing Center
- Founder of AWORDZ Language Engineering, a consultancy/LSP at >10k€ MRR
Adrián Valera Román
- Co-founder & CTO of Nexook (150k+ raised in grants and angel funding)
- Senior Software Engineer in GenAI and cloud (ex-HPE CTO office)
- Technical leadership across early-stage GenAI and analytics companies
- Builder of public projects: Teachy.ie, Dublineros (~20k members) and soti.house
Put your company knowledge to work.
Bring a translation memory and a glossary. We'll run your real content through ACROSS and show you the edit distance against your current process.
- Pilot on your own content, not a generic demo
- Runs inside your existing CAT tool
- Quality baseline measured before and after