Side-by-side comparison of AI visibility scores, market position, and capabilities
Enterprise AI translation platform with agentic LILT Assist. US DoD contract for military-wide translation. $164M raised. 60+ connectors. Founded 2015, Emeryville CA.
LILT is an enterprise AI translation and localization platform founded in 2015 in San Francisco by Spence Green and John DeNero, both researchers with backgrounds in computational linguistics and machine translation from Stanford and UC Berkeley. LILT was founded on the conviction that the future of language services was not fully automated machine translation nor purely human translation, but a tightly integrated human-AI collaboration model that would combine machine speed with human judgment to achieve the highest possible translation quality.\n\nThe platform combines an adaptive neural machine translation engine with a web-based editor that learns from each translator's corrections in real time, continuously improving suggestions for that linguist and domain. LILT Assist, the company's agentic AI tier, automates entire localization workflows — file parsing, translation, review routing, and delivery — through more than 60 connector integrations with CMS, DAM, and product management tools. The company holds a multiyear contract with the US Department of Defense to provide translation services across military branches, covering dozens of languages in sensitive domains.\n\nLILT has raised $164 million in total funding and serves global enterprises in technology, financial services, government, and life sciences. Its DoD contract validates the platform's security posture and translation accuracy in high-stakes environments. With the localization market expanding as enterprises deploy more multilingual AI products, LILT's hybrid human-AI architecture and deep enterprise integrations position it as a differentiated alternative to both legacy translation management systems and commodity machine translation APIs.
Learning experience platform raised $437M total through Series D; AI-powered skill mapping and role-playing simulations; SAP Joule integration coming 2026
Degreed was founded in 2012 with the vision that learning should be continuous, skills-based, and connected across formal education, on-the-job experience, and self-directed development. The company built a learning experience platform (LXP) that aggregates content from thousands of providers — including LinkedIn Learning, Coursera, YouTube, internal systems, and podcasts — into a single interface that employees use to upskill throughout their careers. Degreed's core innovation was creating a common language for skills, enabling organizations to map employee capabilities to role requirements and identify development gaps at scale.\n\nDegreed's platform serves large enterprises and Fortune 500 companies, functioning as the connective layer between HR systems, content libraries, and business skills strategies. Its AI-powered skill mapping identifies employee strengths and gaps from activity data, then surfaces personalized learning recommendations aligned to career goals or business priorities. The platform is introducing AI role-playing simulations and SAP Joule integration in 2026, deepening its footprint in enterprise workflow automation and skills-based talent management. Degreed partners with major content providers and HRIS vendors including Workday, SAP, and Cornerstone to embed learning intelligence across enterprise talent operations.\n\nDegreed has raised $437 million in total through its Series D, with investors including Owl Ventures, Jump Capital, and others who see skills-based talent management as a major enterprise software category. The platform serves millions of employees globally at organizations including Unilever, Visa, Bank of America, and Walmart. As AI reshapes job roles faster than traditional training cycles can respond, Degreed's infrastructure for continuous, skills-mapped learning positions it as essential infrastructure for enterprise workforce transformation.
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