Scaling AI training across 28 languages with Lifted, an Upwork Company™
Lifted helped a global learning platform validate AI-powered products across 28 languages, from 700 to 190,000 sentences.
At a glance.
Summary
As a leading global learning platform expanded its AI and machine learning initiatives, its teams needed flexible access to specialized testers capable of validating new features and tools across languages and markets. Traditional vendor models were too rigid and too slow for fast-paced AI product cycles. Lifted stepped in to design and run a fully managed linguist program, sourcing, onboarding, calibrating, and delivering structured annotation at scale, all under a single agreement.
The Challenges
Evaluating AI output on a global scale
The company needed to evaluate hundreds of thousands of AI-generated sentences across 28 languages. Each sentence required expert-level review to assess fluency, accuracy, and educational suitability, insights that directly impacted model accuracy and learner experience across the platform.
Speed mismatched to development cycles
Traditional talent sourcing simply could not keep pace. Finding qualified contractors with the right linguistic and technical background typically took weeks, time the product team did not have.
Maintaining consistency and accuracy across global test environments
Managing testing across distributed teams led to inconsistent data and variability in how tests were executed. This reduced confidence in results and increased the risk of missed issues or unreliable feedback.
Aligning testing speed with rapid feature releases
Product development cycles were moving faster than traditional testing models could support. Rigid vendor structures made it difficult to scale testing up or down, creating bottlenecks that slowed time-to-market.
Operational complexity in manual coordination
Coordinating freelance linguists independently while ensuring consistent quality, instruction alignment, and bias control created major operational strain. Every new language added complexity; every model update risked introducing inconsistency.
The Solution
The client chose Lifted to build and manage a dedicated linguist bench, not just to fill a gap, but to create a scalable, repeatable infrastructure for AI data work. Lifted’s managed model meant the client could focus entirely on analysis and product outcomes rather than operational overhead.
Lifted handled everything: recruiting and pre-qualifying linguists, onboarding and calibration, project management, quality control, and delivery. The single umbrella agreement removed legal and procurement friction, allowing new languages and evaluation dimensions to be added on demand.
“Lifted makes our day-to-day operations significantly easier for our teams. What stood out most was the ability to put a reliable process in place that runs smoothly without constant follow-up or back-and-forth.”
The Results
By partnering with Lifted, the company gained the speed, precision, and flexibility required to validate AI-driven learning products globally. The result: faster feature launches, higher data reliability, and a dramatically simplified operational model.
Elastic scalability
The program expanded from an initial 700 rows to 190,000 rows, a 27,043% increase, all within pre-approved rates and timelines. The rating model Lifted developed for the program with weekly calibration ensured that quality scaled alongside volume.
Faster iteration with every sprint
From kickoff to full production took days, not weeks. The pre-vetted linguist bench meant no recruiting lag; new evaluation batches could begin almost immediately as product cycles demanded.
Centralized, consistent process
Before Lifted, independent contractor evaluations were fragmented across teams with no unified standard. Lifted’s managed model brought all evaluation activity under a single, consistent workflow.
Expanding adoption across the organization
The success of the program has created momentum beyond the initial team. Positive internal sentiment has led other teams to recognise the model’s potential for their own workflows.
Key success factors:
80+ linguists pre-qualified and ready to deploy across 28 languages
AI training data scaled from 700 to 190,000 rows (27,043% growth)
Full production achieved within days of kickoff, not weeks
Consistent, bias-aware annotation across all language markets
Faster product validation cycles and reduced time-to-market
Improved feedback collection and localization quality
Centralized contractor process, replacing fragmented team approaches
Growing cross-team adoption driven by internal program success
Building the infrastructure for AI at scale
Lifted didn’t just solve an immediate resourcing problem. It built the operational infrastructure that allowed a global learning platform to pursue ambitious AI development goals without being held back by talent acquisition or quality management constraints. With a single vendor, a single contract, and a single delivery model, the client’s team could focus entirely on what they do best: building learning products that work for people around the world. As AI programs grow in scope and ambition, the foundation Lifted has built, vetted talent, calibrated quality, elastic capacity, is ready to scale alongside them.
While this work was performed when these Enterprise solutions were embedded in Upwork, the same offerings and more are now available through Lifted, an Upwork Company.
