List of Lilt Customers
Emeryville, 94608, CA,
United States
Since 2010, our global team of researchers has been studying Lilt customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Lilt for ML and Data Science Platforms from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Lilt for ML and Data Science Platforms include: Federal Bureau of Investigation, a United States based Government organisation with 35000 employees and revenues of $9.75 billion, Box, a United States based Professional Services organisation with 2810 employees and revenues of $1.09 billion, National Weather Service, a United States based Professional Services organisation with 20 employees and revenues of $4.0 million and many others.
Contact us if you need a completed and verified list of companies using Lilt, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Lilt customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Box | Professional Services | 2810 | $1.1B | United States | LILT | Lilt | ML and Data Science Platforms | 2024 | n/a |
In 2024, Box integrated Lilt using the Lilt <> Box Connector to embed Lilt's AI translation directly into Box content workflows. Lilt is an application in the ML and Data Science Platforms category and the integration targets content management and localization efficiency for Box enterprise content and CMDB use cases.
The implementation automates file transfer and trigger based translation initiation so assets stored in Box enter Lilt translation pipelines without manual handoffs. Functional capabilities implemented focus on machine translation orchestration, automated ingestion of Box files, and synchronization of translated assets back into Box content repositories.
Technically the connector maps Box content lifecycle events to Lilt translation workflows, enabling translation triggers driven by content state changes and metadata. Operational coverage concentrates on enterprise content and localization teams responsible for content publishing and asset localization within Box.
The Lilt <> Box Connector was showcased at BoxWorks 2024 and the partnership was announced in November 2024, indicating a coordinated rollout for customers. Partners highlighted outcomes of faster time to market and reduced manual handoffs for translated assets in Box.
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Federal Bureau of Investigation | Government | 35000 | $9.7B | United States | LILT | Lilt | ML and Data Science Platforms | 2022 | n/a |
In 2022 the Federal Bureau of Investigation implemented Lilt within its ML and Data Science Platforms portfolio to run generative AI translation pilots aimed at scaling language processing for internal documents and external communications. Lilt was deployed to support government operations language workloads and public sector communications within the FBI environment.
The implementation emphasized translator in the loop review workflows combined with Lilt’s generative translation capabilities, and included configuration of workflow orchestration and quality control modules to maintain human oversight. Security measures were built into the deployment to enforce strict data purge policies and access controls consistent with law enforcement data handling requirements, reflecting ML and Data Science Platforms practices of model-assisted translation with gated human review.
The engagement was scoped as a United States law enforcement and public sector implementation executed through pilot rollouts and later discussed in a joint webinar and recap published in 2023. Governance focused on translator in the loop review and data purge controls, and the FBI reported measurable translator efficiency gains across multilingual workloads in government operations use cases.
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National Weather Service | Professional Services | 20 | $4M | United States | LILT | Lilt | ML and Data Science Platforms | 2021 | n/a |
In 2021, the National Weather Service began pilots using Lilt to provide AI-powered translation technology for multilingual forecasts, warnings and outreach. Lilt was deployed as an ML and Data Science Platforms solution to automate translation workflows, with initial focus on Spanish and Simplified Chinese for U.S. communities with limited English proficiency.
The implementation integrated Lilt's machine translation capabilities into forecast and alert content pipelines to enable automated translation of storm products and public safety messages. Phase one of an experimental multilingual weather.gov site launched in 2023, representing a staged move from pilot translations to public-facing multilingual content across selected forecast product types.
The program was operated as an experimental pilot with phased rollout across languages and prioritized product types to align with regional outreach needs and emergency communications. The National Weather Service reported that translation time for certain storm products fell by over 83 percent, a result cited as improving regional public-safety communications.
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Buyer Intent: Companies Evaluating Lilt
- Modern Aviation, a United States based Transportation organization with 210 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
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