Straker (STG) Generative AI Summit Presentation summary

Generative AI disruption and industry challenges

• Generative AI (genAI) is perceived as disruptive, raising concerns about its impact on traditional translation and localisation business models.

• GenAI excels in major languages but struggles with less common ones, and is prone to hallucinations and factual errors.

• Human insights remain critical, as genAI lacks the ability to provide nuanced, context-driven judgment.

• Industry interest is shifting from content generation to quality evaluation and verification workflows.

• Cost efficiency and process simplification are key drivers for adopting AI-enabled solutions.

AI-powered solutions and workflow innovations

• Developed a genAI fact-checker and quality estimation engine using proprietary language data and models.

• Introduced Automated Post Editing (APE) where multiple LLMs collaborate to refine translations, with human verification as a final step.

• Orchestrate AI workflow builder allows customers to configure translation processes based on budget and quality needs.

• The Verify AI Agent process flow integrates LLM content generation, quality evaluation, automated post-editing, and human review.

• Six key components: LLM content generation, SLM quality evaluation, multi-LLM refinement, human verification, configuration engine, and token-based payment.

Business model transformation and cost structure

• Traditional model: machine translation plus human review, charged per word or hour, resulting in higher total costs.

• New model: token-based charging for LLM content generation, quality evaluation, and automated post-editing, with human verification as needed.

• Example cost comparison shows significant reduction in total cost using the AI-driven workflow.

• Pricing disruption accompanies technological disruption, moving from per-word to token/character-based billing.

• Customers can tailor workflows to balance cost and quality, triggering human review only when AI quality falls below thresholds.