Automating translation projects

Qabiria was born with a very specific mission: allowing people and companies to communicate without misunderstandings, with a level of quality that holds up even when the text ends up in the hands of users, customers, regulators, or lawyers.

Then came artificial intelligence. Around 2022 it started to become really useful in daily work: not as a “magic wand”, but as an accelerator for repetitive activities, checks, extractions, normalizations, analyses. Less wasted time, more attention to language choices and project management.

From there, our next step was natural: use automations and integrations to smooth the entire life cycle of a translation or localisation project.

What can be automated in a translation project

Let’s take a “standard” project (file sent by the client, analysis, quote, assignment, production, QA, delivery, feedback). Almost every stage can benefit from some degree of automation. Some automations may be straightforward; others require a minimum of planning.

1) Receiving files

Goal: getting the materials to the right place, with the minimum information needed to work well.

Typical automations:

• upload via portal or dedicated form
• ingest from email (attachments saved in default folders)
• monitoring of cloud folders (Drive, OneDrive, Dropbox)
• automatic renaming of files according to agreed rules (client, language, version)

The result: fewer situations like “I’m sending it back to you because the attachment was missing” and fewer endless email backs and forths.

2) Material analysis and pre-quoting

Goal: understand what’s inside the files and estimate times and costs with clear criteria.

Typical automations:

• counting words and segments
• analysis of repetitions and comparisons with translation memories
• language and variant detection
• pre-classification by content type (marketing, technical, legal, UI, etc.)
• automatic generation of an internal report for the project manager

If you work with many formats, this stage is where hours upon hours are burned. Automating it makes all the difference.

3) Planning and assignment

Goal: assign work to the right people and make it flow smoothly.

Typical automations:

• project template (translation + proofreading + QA + layout, depending on the project)
• assignment based on skills, language, domain, and availability
• synchronization with calendars and deadline management
• automatic notifications when status changes (email, Teams, Slack, etc.)

Here we seek the PM's serenity to increase his real control over the project.

4) Production (translation and review) + language resources

Goal: make the tools work together, with terminological consistency.

Typical automations:

• connection to CAT tool, memories and glossaries
• continuous updating of resources (without copies scattered around)
• pre-translation where it makes sense (based on content and policy)
• AI-powered suggestions and checks, with human review

The important part remains in the hands of those who translate and revise. The most mechanical work is entrusted to automation.

5) Monitoring and risk management

Goal: always know where you stand and catch problems before they explode.

Typical automations:

• dashboard with real-time progress
• alerts on risky deadlines and bottlenecks
• triggers on anomalies (missing files, corrupt formats, blocks under revision)
• log and version tracking.

When the project grows, this stage can prevent panic.

6) Quality control and delivery

Goal: deliver clean, consistent, and technically correct files.

Typical automations:

• automatic QA on terminology, numbers, tags, punctuation, formatting
• format-specific controls (HTML, XML, InDesign, subtitles, etc.)
• delivery via secure channels with confirmation of receipt
• automatic storage of deliverables and updated resources

Here, automation helps prevent trivial and often costly errors.

7) Feedback and continuous improvement

Goal: make the most of the recently completed project.

Typical automations:

• request feedback with a short survey
• automatic reports (what went well, what is repeated, what to improve)
• updating and synchronizing glossaries and memories
• lessons learned saved in a shared system

This step prevents you from repeating the same mistake several times in a row. It may seem trivial, but it is actually very rare.

TMS/TBMS vs low-code and no-code: how to choose without getting hurt

There are basically two ways to implement the automations shown above: using an integrated management system or connecting several independent systems with low-code or no-code tools.

Many agencies and language departments use integrated management systems, often called TMS or TBMS, Translation (Business) Management Systems. They offer a centralized flow: customer portal, supplier portal, assignments, tracking, QA, reporting, billing, etc.

Pros:

• end-to-end consistency and control
• standardization of processes
• traceability and governance

Cons:

• costs and complexities that can weigh on SMEs and small teams
• limited integrations with tools outside the TMS perimeter

The low-code/no-code solutions (Make, Zapier, Power Automate, n8n and the like) work well when you need them:

• connect tools already in use (CRM, ticketing, cloud, BI, chat)
• build tailor-made flows
• starting gradually, with smaller budgets

Pros:

• flexibility and speed
• integration with existing business ecosystems
• targeted automations, without changing everything

Cons:

• planning is needed: poorly implemented workflows become technical debt
• quality and security require attention (permissions, logs, privacy)

Often the best choice is a hybrid approach: a “central” system for language processes and low-code automations to integrate with the rest of the company.

Practical examples for SMEs and freelancers with recurring volumes

Case A: “We get requests via email and we lose pieces”

Typical solution:

• rules on dedicated email box
• automatic saving of attachments in the project folder
• task creation in a tool (Trello, Asana, Jira, etc.)
• notification to the PM with link and metadata

Case B: “Same customer, same materials, same mistakes”

Typical solution:

• centralized and updated glossary
• Automatic QA before delivery
• reports of recurring non-compliance
• update translation memory at the end of the project

Case C: “We produce content in multiple languages, with marketing and product each working independently.”

Typical solution:

• shared workflow with statuses and responsibilities
• mandatory briefing template
• tracked approvals (who said yes, when, on which version)
• automatic delivery and versioning

Summary table

Stage	TMS/TBMS	Low-code / no-code
File reception	Portals, email/FTP integration	Cloud monitoring, email parsing, event triggers
Analysis	Counts, comparison with TM, reports	External APIs, custom dashboards, custom classifications
Scheduling	Templates, rules, centralized visibility	Custom calendars and notifications, dynamic timelines
Resource assignment	Integrated database	Integrations with HR/CRM tools, alerts on chat and email
Production + QA	Integrated CAT/TM/QA	API connections, external controls, automatic reporting
Monitoring	Native dashboards and alerts	Power BI / Looker Studio, custom notifications and triggers
Delivery	Secure portals, tracking	Cloud flows + mailing + confirmations and archiving
Feedback and resources	Centralized collection and management	Survey + reports, sync materials to cloud, ad hoc routine

Do you really want to automate? It starts with a map, not a tool

If you're thinking, “OK, cool, where do I start?”, the answer is always the same: map the real process (the one you do today), then choose what to automate first.

Usually the first candidates are:

• file ingest and briefing collection
• pre-analysis and report
• notifications and status changes
• Pre-delivery QA