Adam Bittlingmayer, CEO and co-founder of ModelFront, joins SlatorPod to discuss the state of the art in enterprise AI translation and the language technology platform’s (LTP) launch of an AI-native open translation management system (TMS).
Bittlingmayer says translation can appear solved when an AI model is given enough context and the right prompt, but providing that context consistently within complex enterprise localization workflows remains difficult. Enterprise teams must account for different products, content types, terminology, quality requirements, languages, and existing systems.
The CEO revisits ModelFront’s core value proposition of using AI to check and fix AI, allowing enterprises to automatically approve translations that would otherwise require human review. Focused on high-stakes localization workflows, the LTP takes responsibility for translation quality and the engineering complexity behind it. He also highlights its outcome-based pricing model, under which customers pay only for translations that the LTP successfully approves.
Bittlingmayer also talks about why neural machine translation models remain widely used despite advances in LLMs. He says newer models can benefit from much richer context, but existing enterprise workflows and software often make providing that context difficult. He sees verification as increasingly important as AI-generated content and translation volumes continue to expand.
Bittlingmayer then introduces ModelFront’s AI-native open TMS, OpenLoc, which the company is making available for free, with hosting offered at cost. He argues that traditional TMSs were not designed for today’s AI workflows, creating friction that can encourage teams to bypass centralized localization processes altogether.
He says the new platform is designed around openness, flexible AI use, prompt building, and MCP connectivity, allowing users to interact with localization workflows through enterprise AI assistants as well as the traditional interface. Bittlingmayer sees this as part of a broader goal to make AI more accessible while improving enterprise AI outcomes.
ModelFront is launching OpenLoc through an early access program, with general availability planned to follow.
