
The platform Bloomberg's localization team already trusts. Now for every team.
Bloomberg’s localization team has trusted LILT since 2017, running financial content through one adaptive platform in Korean, Japanese, and Simplified Chinese. As Bloomberg expands into private markets, AI-driven products, and new regions, extend that proven quality and speed to every team: News, Law, R&D, HR, and beyond, on one governed platform that replaces generic MT and point tools, so quality stays high and translation memory savings compound across Bloomberg.
Kim Barnes
Your Enterprise Account Executive
Alex Bougher
Your Customer Success Manager





Use cases
How every Bloomberg team wins with LILT
Financial content, translated to standard
Localize market news, research, and financial content, including the fast-growing data and research behind Bloomberg's newer products, in Korean, Japanese, and Simplified Chinese to the quality standard your editors already hold LILT to.
Expand to every Bloomberg team
Take the platform your localization team runs daily to News, Law, R&D, HR, and L&D, one standard as Bloomberg grows into private markets and new regions, instead of a different tool per department.
Design and publishing (DTP)
Translate inside LILT and hand back print-ready InDesign layouts through secure delivery, adding design and publishing to the same workflow.
Govern your AI-generated content
As AI-driven products create more content faster, keep it on-terminology and on-brand with adaptive models, expert review, and AI review built in.
Self-serve for internal translators
Your in-house translators work directly in the platform, with glossaries and translation memory they manage themselves and reuse across every project.
Replace generic MT and point tools
Consolidate the DeepL and SDL pockets across departments onto one governed, secure platform with full visibility into spend and savings.
Built on quality Bloomberg can measure
Quality you can measure
MQM scoring against a 95% threshold, with the review workflows and arbitration your team already relies on.
Built for sensitive financial data
Your content and custom models stay isolated and are never used to train public AI, with enterprise security for market-moving information.
A tech company, not just an LSP
The reason Bloomberg chose LILT in 2017: a real platform with the reliability, SLAs, and turnaround your editorial deadlines demand.
Savings that compound
Translation memory and glossaries you own, reducing cost with every project as your custom models keep improving.
One adaptive platform, not generic machine translation
News and other teams reach for DeepL because it is fast, but generic MT plateaus on quality, cannot learn your terminology, and offers no managed workflow or security controls. LILT is an adaptive enterprise platform: custom models that improve from every edit, expert review, and the governance a company like Bloomberg requires.
Model
Your terminology
Human review
Security and data
Workflow and reach
Analytics
Built for how Bloomberg works
LILT fits the workflow your teams already run, from in-platform translation to design and publishing, with the API and governance to scale across departments.
In-platform glossary and translation memory
Your team manages glossaries and translation memory directly in LILT, reused across every language and project.
Design and publishing (InDesign)
Send content for translation and get back print-ready InDesign layouts through secure delivery.
API and AI assistants (LILT MCP)
Connect Bloomberg systems through the LILT API, and reach LILT from the AI assistants your teams use via LILT MCP.
Bring every Bloomberg team onto the platform your localization team already trusts.
You have run financial content through LILT for nearly a decade. As Bloomberg grows into private markets, AI-driven products, and new regions, extend that same quality, security, and turnaround to News, Law, R&D, HR, and beyond, on one platform with the savings and visibility to grow with confidence.


