Tech & AI Solutions
AI-Powered Machine Translation
Controlled use of machine translation for content types where it can deliver value without compromising quality.
Machine translation has improved significantly and can contribute real value in the right context. It is also inappropriate or insufficient for many content types. We help organizations assess where machine translation can be used responsibly and how to integrate it with human review to produce usable output.
Machine Translation Works Best When Used Deliberately
Not all content should be processed through the same machine translation workflow. The appropriate approach depends on the content type, audience risk, publication context, and quality requirements. Internal-only documents may tolerate a different level of automation than customer-facing content or regulatory submissions.
We provide machine translation implementation as part of broader translation workflows, always with a clear plan for human review, terminology integration, and quality control. We do not position machine translation as a replacement for expert human judgment — we position it as a tool that can improve throughput when applied appropriately.
What's Included
A complete approach to ai-powered machine translation
Content Suitability Assessment
Evaluation of content types to determine where machine translation can be applied and where it would create unacceptable quality or risk.
Engine Selection
Selection of the appropriate machine translation engine based on language pair, content type, and performance characteristics.
Terminology Integration
Integration of approved client terminology into the machine translation workflow to improve consistency of output before human review.
Controlled Machine Translation
Configuration of machine translation workflows with appropriate output controls, including domain settings and content filtering.
Human Validation
Post-editing review by specialist linguists to correct errors, improve fluency, and ensure the output meets the quality requirements of the intended use.
Quality Monitoring
Ongoing monitoring of machine translation output quality to identify degradation, engine issues, or content types requiring closer review.
Process
How it works
Content and Risk Assessment
We evaluate the content types, audiences, publication context, and quality requirements to determine which content is appropriate for machine translation workflows.
Engine and Workflow Selection
The appropriate machine translation engine and Post-Editing workflow are selected based on language pair, content type, and required output quality.
Terminology and Resource Preparation
Approved terminology, glossaries, and translation memories are prepared and integrated into the MT workflow to improve baseline output quality.
Human Review and Post-Editing
Machine-translated content is reviewed and corrected by specialist post-editors, with the level of editing determined by the quality requirements of the content.
Performance Monitoring
Output quality and workflow efficiency are monitored to ensure the MT and Post-Editing process continues to meet requirements as content volume and type evolve.
Why Randa Translation
What sets our approach apart
Appropriate Use, Not Maximum Automation
We assess what machine translation is suited to before applying it, rather than applying it to everything for cost reduction.
Human Review Always Included
Machine-translated content always passes through human review calibrated to the content type and intended use.
Terminology Integration
Approved client terminology is integrated into the workflow so machine translation output reflects the organization's established language.
Transparent About Limitations
We are clear about where machine translation is not appropriate and will recommend a different approach rather than apply it regardless.
Build a Smarter Translation Workflow
Tell us about your content types, volume, and quality requirements. We will assess where machine translation can add value and how to integrate it responsibly.