Andela is buying Woven, a New York-based technical assessment firm, in a deal aimed at tightening how companies test whether software engineers can actually perform on the job as artificial intelligence moves from pilots to production.
The acquisition gives Andela deeper tools to predict real-world performance and AI fluency across its marketplace of more than 150,000 engineers, as clients demand proof that talent can build, deploy, and run AI systems at scale.
Founded to mirror day-to-day engineering work, Woven designs assessments built around realistic scenarios rather than abstract puzzles. Its software scores candidates using detailed rubrics and machine learning models trained on years of performance data. That capability will now be folded into Andela’s hiring and matching platform.
Wes Winham Winler, Woven’s founder and chief executive, will join Andela to lead the development of new assessments focused on AI-assisted software development and AI system design. Andela said the goal is to forecast how engineers perform once embedded inside customer teams, not just how they test.
Companies deploying AI at scale tend to need three profiles. Engineers who build models and agents from business requirements. Engineers who stitch models, data, and tools into automated workflows. Engineers who keep those systems stable, compliant and governed in production. Andela said Woven enables it to measure and place talent in each role with greater precision.
“To power the AI ecosystem at scale, the world needs AI native, enterprise ready engineering talent en masse,” said Carrol Chang.
Andela also gains Woven’s library of scenario-based tests, tools to generate new assessments using AI, and its founding team. The scoring system is designed to remain consistent as hiring volumes rise, a key concern for large employers.
Woven’s technology sits on top of Qualified, an assessment platform Andela bought earlier. The combined stack creates a single system for testing engineering fundamentals and AI-specific skills.
“Andela already had the talent network and upskilling muscle,” Winler said. “This lets us measure real performance in the AI era.”
