Two Healthcare Giants Join Forces in Landmark Interpretation Merger

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July 3, 2025

Propio and CyraCom Merge in Major Healthcare LSP Dea

A New Powerhouse in U.S. Language Access

Propio Language Services has acquired CyraCom International Inc., uniting two of the most prominent U.S.-based interpretation providers. The move reshapes the healthcare language access landscape, combining Propio’s tech-driven platforms with CyraCom’s decades of experience in clinical interpretation.

Both companies rank among the world’s largest LSPs in the 2025 Nimdzi 100. Propio entered the Top 10 at #10, while CyraCom maintained a solid presence after ranking #19 in 2024. Their merger consolidates two influential forces in the healthcare interpreting market and signals a shift in the industry’s competitive landscape.

CyraCom built its reputation through over-the-phone and video services, especially in settings where clarity is crucial. Propio, in contrast, has prioritized AI automation and secure tools like Propio ONE and Workforce OS®.

What This Means for Clients and Interpreters

Together, the merged companies will serve over 12,000 clients through a network of 20,000 linguists working in 300+ languages. More than a numbers game, the merger creates a platform that integrates automation, compliance, and human expertise at scale.

“This is a transformative moment in our industry,” said Marco Assis, CEO of Propio. “Together, we’ll set a higher standard for access, speed, and quality.”

Clients can expect smoother workflows and quicker onboarding, particularly in healthcare, insurance, and government sectors. For interpreters, the shift may bring better systems and increased demand for remote work.

A Signal of Larger Industry Shifts

As integration progresses, many will watch how Propio maintains its tech-first model while incorporating CyraCom’s training standards. Still, one thing is certain: in a post-pandemic world where healthcare equity depends on language access, this deal could redefine service delivery.

The acquisition also reflects broader consolidation across the language industry. Rising demand for scalable, tech-integrated solutions is driving major players to join forces.

The merger also enhances both companies’ ability to invest in interpreter support, compliance tools, and multilingual service expansion. As healthcare providers face growing linguistic diversity, the combined strengths of Propio and CyraCom may help institutions meet regulatory requirements while ensuring that patients receive clear, accurate communication in their preferred language. This development adds to the evolving landscape of healthcare interpretation.

Welo Data Unveils New Framework for Evaluating Causal Reasoning in Large Language Models

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MultiLingual Staff

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July 2, 2025

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Welo Data has released a new research study examining how different scoring methods and prompt structures influence the evaluation of causal reasoning in large language models (LLMs). Titled “A Novel Multi-Select Framework for Evaluating Causal Reasoning in LLMs,” the study introduces a framework for testing how well LLMs identify multiple causes—including confounders and contributing factors—across a range of prompt types.

Unlike many existing benchmarks that rely on binary or single-answer formats, this study uses multi-select questions, requiring models to identify all valid answers from a list of options. The research team evaluated eight state-of-the-art LLMs using 576 prompts, spanning three causal question types and two prompting formats (standard and chain-of-thought). Five distinct scoring metrics were applied to assess performance from multiple angles: precision, recall, F1 score, complement, and a “trapdoor” metric that penalizes any incorrect selection.

“This research shows just how much our conclusions about AI performance depend on the lens we use,” said Dr. David Harper, Data Scientist at Welo Data and lead author of the study. “If we’re serious about building high-performing reasoning models, we need evaluation methods that reflect the complexity of the real world.”

Key findings from the study include:

Scoring methods significantly impact model rankings. Metrics like precision and recall reveal different strengths, and complement scoring offered the clearest separation among models. The trapdoor metric—where a single incorrect choice nullifies a response—exposed over-selection tendencies in some models. Of the eight models tested, only two maintained the same ranking tier across all five metrics.
Models struggle with causal completeness. Most models demonstrated conservative selection strategies on causal questions—averaging just 2.7 to 3.6 selections, compared to 5.5 expected selections. In contrast, models adopted overly liberal strategies when identifying confounders, selecting up to 4.7 options when, on average, 2.5 were correct.
Chain-of-thought prompting showed no benefit in multi-select tasks. Contrary to previous research suggesting it improves reasoning, this study found no consistent performance improvement when chain-of-thought instructions were added.
Behavioral patterns vary by model family. Some models exhibited more cautious, precision-oriented selection behavior, while others were more liberal and risk-prone—particularly when evaluating non-causal relationships.

This study underscores a single, practical takeaway: evaluation methods must mirror the specific reasoning behaviors we want LLMs to demonstrate. As these models take on high-stakes tasks—such as diagnosing diseases, flagging fraudulent transactions, and guiding scientific discovery—organizations need tests that expose how a model actually reasons, not merely whether it selects the correct answer, to ensure safe and dependable deployment.

For more information, visit welodata.ai.

About Welo Data

Welo Data, a division of Welocalize, stands at the forefront of the AI training data industry, delivering exceptional data quality and security. Supported by a global network of over 500,000 AI training professionals and domain experts—along with cutting-edge technological infrastructure—Welo Data fulfills the growing demand for dependable training data across diverse AI applications.

Its service offerings span a variety of critical areas, including data annotation and labeling, large language model (LLM) enhancement, data collection and generation, and relevance and intent assessment. Welo Data’s technical expertise ensures that datasets are not only accurate but also culturally aligned, addressing significant AI development challenges like minimizing model bias and improving inclusivity.

Its NIMO (Network Identity Management and Operations) framework guarantees the highest level of accuracy and quality in AI training data by leveraging advanced workforce assurance methods.

Copyrighted Books Ruled Fair Game for AI Training at Meta and Anthropic

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MultiLingual Staff

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July 2, 2025

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United States judges affirm that digitizing and training LLMs on published books falls under fair use

Meta’s Llama and Anthropic’s Claude can legally be trained on copyrighted books, according to two recent US court decisions that mark a pivotal moment in the legal debate surrounding large language models (LLMs) and intellectual property (IP). In lawsuits brought by authors who claimed their works were used without consent, both companies successfully defended their artificial intelligence (AI) training practices under the doctrine of “fair use,” a critical concept in US copyright law.

Training LLMs is “transformative,” not derivative

Anthropic’s case hinged on its practice of purchasing physical books, digitizing them into a searchable library, and using that library to select training material for Claude. In a June 23 ruling, US District Judge William Alsup found that both the digitization and the model training qualified as fair use. He reasoned that Anthropic did not alter the creative content of the books or share them publicly. Instead, it changed their format and used them in a new context: AI training.

Judge Alsup emphasized that the Copyright Act protects derivative works that involve new creative material — such as translations, dramatizations, or adaptations — but that LLM training does not fall into that category. The act of distilling patterns and structure from a large corpus, he concluded, is transformative rather than exploitative.

This distinction may also affect translation rights. The ruling suggests that LLM-generated translations of books would still require approval from copyright holders, but scanning and training on already translated versions would likely be considered fair use.

Style isn’t copyrightable, but expression is

A separate case involving Meta’s Llama yielded a similar result. On June 25, federal Judge Vincent Chhabria ruled against a group of 13 authors who alleged that Meta’s LLM was trained to “regurgitate” their works and compete with human-created content.

Judge Chhabria rejected this, noting that Llama would not reproduce more than 50 consecutive words from any copyrighted book and was instead trained to emulate writing styles. He clarified that while style is not protected by copyright — specific expression is — and there was no evidence that Llama replicated identifiable passages verbatim. He added that LLMs are “innovative tools” capable of many tasks, including translation, but not designed to generate entire works that directly compete with original authors.

Implications for AI, publishing, and localization

These rulings set a strong precedent in favor of AI developers, reinforcing the notion that training LLMs on copyrighted books — without reproduction or distribution — falls within legal bounds. However, it leaves key questions unresolved, especially regarding full-text outputs, translations, and derivative content across languages.

For the localization industry, the distinction between style, structure, and expression may become increasingly relevant as AI tools are used to support multilingual content creation. If AI-generated translations are treated differently from original training material, legal clarity will be needed on who holds the rights to translated outputs.

The debate has extended beyond the courtroom. In a June 28 episode of the All In Podcast, David Sacks — former “AI Czar” under the Trump administration — voiced his support for the rulings, stating that “if an AI model violates someone’s copyright by outputting something that’s identical, then obviously that’s a violation. But if all they’re doing is transforming the work… then that is not a violation of copyright.”

10 Lesser-Known Jobs in the Language Industry

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Sydnee Cooper

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July 2, 2025

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The language industry is always evolving to meet the needs of consumers around the world by creating unique avenues for language professionals to provide solutions. In addition to common job titles — such as translator, interpreter, account manager, and quality assurance specialist — many lesser-known roles exist in the industry. This article highlights ten career paths that you may not have heard about, but that offer exciting opportunities. By combining language and localization skills with other in-demand skill sets, such as human resources (HR) or information technology (IT), you just might find your perfect professional fit.

1. Language Lab Manager

Language lab managers help train future translators and interpreters, including students at language flagship-supporting universities (as designated by the United States (US) Defense Language and National Security Education Office). With each flagship university focusing on a specific language, language labs often become a critical avenue for implementing language curriculum in real time. These language labs are run by professionals who possess both IT skills and a background in teaching foreign languages. Language lab managers hold the key for students to access foreign language resources that are not available outside of the university.

2. Language Cataloging Specialist

Language cataloging specialists generally work with an American university’s Cataloging and Metadata Services Department for long-term contracted positions that focus on a specific language within the library based on existing collections. Primary responsibilities generally include creating, processing, and revising target language records within the library system according to standard practices encouraged by the US Library of Congress. Catalogers play a crucial role within the language industry by allowing readers access to global material originating from other languages and time periods. These professionals often need a minimum of a master’s degree along with a target language proficiency certification.

3. Director of Curriculum Assessment

In the US, nationally recognized organizations such as The College Board set the standards for high school and college curriculum in all subject areas, including foreign language. The College Board administers exams such as Advanced Placement (AP) to give students the chance to verify their knowledge in subject matter areas in exchange for college credit. AP exam criteria must be vetted by experts before the tests are administered to students. That is why, for each of the 11 AP language exams, there is a director of curriculum assessment who at a minimum possesses a master’s degree in the target language or a directly related discipline with years of experience. The director’s main responsibilities include assessing the presented exam curriculum as it pertains to current linguistic use, training educators to adequately author the test, and leading the successful scoring of the student exams. This sets the academic standard for the next generation of language learners who wish to further their language skills by certifying their knowledge.

4. Market Research Analyst

A major reason for rapid growth in the language industry is up-to-date data that is made available by market research analysts. As a professional market researcher for the language industry, you allow stakeholders to better understand the current market landscape in its entirety by providing an aerial view through various research models. This gives the industry time and space to adjust how it conducts business for a more competitive edge. This work can often be seen in companies dedicated to providing crucial market intelligence, such as Nimdzi Insights. Some of the main responsibilities of this role are being able to adequately examine language industry market trends and demographics to properly advise companies on product optimization, advertising channels, and pricing. This is a perfect career path for those with a passion for language and studying market conditions who want to help companies grow.

5. Linguistic Field Worker

Linguistic fieldwork is necessary for better understanding the role language plays in a society or community. This job is more than just the documentation of endangered languages in remote villages. It involves the collection of accurate data on a language with the goal of understanding how it affects that specific group of speakers. Fieldwork can be conducted inside and outside the natural environment, as the primary focus is analytical use with a strong emphasis on ethics. Therefore, fieldwork can take place in a classroom setting, corporate office, or even town hall meeting. Most professionals who undertake linguistic fieldwork as a career become university professors, which increases the odds of getting ethics approval and funding to support your work. As the concept of fieldwork has gained more attention over the past decade, this profession is perfect for those who wish to dedicate their careers to preserving languages and better understanding language loss.

6. Language Access Coordinator

Language access coordinators (LACs) in the US identify language accessibility needs within the jurisdiction they serve and create tailored solutions that break down language barriers for non-English-speaking, limited-English-proficient, deaf, and hard-of-hearing communities. These professionals provide pipelines to language service providers (LSPs) by implementing funding regulations across city, state, and federal levels through the creation of procurement opportunities. LACs are responsible for overseeing pre-approved budgets for language access programs, as well as assessing diverse linguistic needs. They are also responsible for evaluating language service contracts and for quality assurance. This is the perfect job for those who have a passion for language, civil rights, and social action.

7. Linguistic Recruiter

Linguistic recruiters are responsible for supplying LSPs with qualified vendors so that they are able to contract them out to entities who need professional language services. Recruiters generate analytical and well-documented linguist sourcing, recruiting, and selection reports and metrics. They source qualified professionals for specific teams and projects all while building and maintaining long-term relationships. They are responsible for facilitating orientation, testing, on-boarding, and follow-ups, all while managing the company’s list of contracted and full-time linguists to successfully complete language service requests. Most notably, recruiters are responsible for reporting and analyzing current on-site translation needs to identify recruitment needs as they evolve. Not only does a linguistic recruiter need to be familiar with national translation and interpreting standards for each industry, but they should also have a passion for statistics and helping new team members through HR-style work.

8. Language Museum Director

In addition to preserving the world’s languages and cultures through research and documentation, language museums play an important role in providing the public with unique ways to learn about language. There are currently more than 55 established language museums across the globe that cover every component of human language. Being a museum director requires candidates to hold advanced degrees along with extensive training in either education or museum and cultural studies. These professionals have a passion for both public service and language education.

9. Cultural Trainer

Cultural trainers come from many backgrounds, but ultimately provide the same crucial service of relaying expectations and practices across foreign cultures for the purpose of helping people understand one another in the workplace. Whether this be in high-stakes environments, such as the federal government or a corporate office, or in educational settings such as a classroom or conference, cultural trainers bridge gaps between cultures through tailored curriculum that caters to the learning needs of the target audience. They must assess learners’ progress through tests, assignments, and interactive activities that promote cultural immersion, all while developing cultural awareness and sensitivity to the target culture. Trainers are responsible for providing feedback to learners that encourages cultural understanding as it evolves in the workplace. These professionals are critical to overcoming language learning and cultural barriers in our globalized world. Generally, candidates must possess fluency in two or more languages and have a minimum of a bachelor’s degree.

10. GIF Creator for International Languages

A Graphic Interchange Format image (GIF) is a type of media file that displays an animated picture with no sound. As most cellphone users know, GIFs are commonly used in text messaging apps. However, for those who do not read or write in English, using this form of communication can be difficult due to language and cultural barriers. Therefore, GIF creators are needed to convey the intended meaning from the source language into the target language. In addition to translating pre-existing GIFs, these professionals are expected to create new ones for global clients that match with current linguistic and cultural trends. Qualified candidates are expected to possess professional-level proficiency in both the target and source language, along with knowledge of creative software common with GIF creation processes.

Ensuring Quality and Ethics in AI Localization Workflows

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Rishi Anand

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July 2, 2025

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The rise of artificial intelligence (AI) in localization brings remarkable gains in speed and scalability, but also demands rigorous quality assurance (QA) and ethical vigilance. As machine translation (MT) and generative AI become commonplace, localization teams must ensure that machine output meets cultural and linguistic expectations and that AI processes uphold transparency, accountability, and respect for user privacy.

Despite advances in MT, machines can misinterpret idioms, handle context poorly, and overlook cultural nuances. Specialized domains and unique language pairs continue to challenge even the most sophisticated engines. Blind trust in machine output risks errors that harm brand reputation and user experience, underscoring the importance of human review at critical junctures.

Effective workflows pair AI with human expertise through a clear, three-stage process:

Automated Quality Estimation: MT systems now offer confidence scores that flag low-rated segments. Linguists review only those portions marked as uncertain, focusing effort where errors are most likely.
Terminology and Style Control: Centralized glossaries and style guides ensure consistent use of brand terms, tone, and voice. AI suggestions are cross-checked against these resources before approval.
Post-Editing Guidelines: Detailed instructions distinguish minor copyediting from full rewrites, helping reviewers maintain speed without sacrificing accuracy.

Moreover, machine-learning models mirror the data on which they are trained, carrying risks of bias and cultural insensitivity if left unchecked. Localization teams should adopt these ethical guardrails:

Transparency With Clients: Describe which parts of a project rely on MT and which undergo human review. For high-stakes content — such as legal, medical, or financial — offer human-only options.
Accountability Protocols: Require human sign-off on final translations. Maintain detailed records of review decisions and version histories within the translation management system.
Bias Detection and Cultural Sensitivity: Regularly inspect AI outputs for pattern-based errors, gendered language issues, stereotypes, and off-color translations. Use diverse reviewer teams to spot culturally specific pitfalls.
Privacy and Data Security: Handle client and user data in compliance with relevant regulations. Anonymize sensitive content before processing on third-party AI platforms and secure all data transfers.

Finally, ethical and quality considerations must evolve alongside technology. To keep processes robust, employ the following:

Feedback Loops. Capture reviewer corrections in a structured database so your AI models learn from past errors. This continuous training improves future accuracy and reduces review effort over time.
Ongoing Training. Provide linguists with workshops on interpreting confidence scores, applying style guides and spotting AI-generated bias. A well-trained team reinforces both speed and quality.
Regular Audits. Schedule periodic reviews of your AI-led workflows. Compare error rates and turnaround times, and adjust quality thresholds based on real-world outcomes.

As localization services integrate AI more deeply, QA and ethical oversight become strategic imperatives. By combining machine-driven automation with targeted human review, teams can maintain clear accountability and embed bias checks and data-protection measures, thereby building reliable and responsible workflows. This integrated approach not only preserves translation quality, but also earns client trust, positioning localization providers to meet global demands with integrity and precision.

Language Services for the Francophone Kaleidoscope

By

Sydnee Cooper

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July 1, 2025

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The Francophone world resembles a linguistic kaleidoscope, reflecting its own diversity of colors that have been shaped by blending centuries of history, culture, and multilingualism. As the fifth-most spoken language in the world with more than 300 million speakers, French can be found in just about every corner of the globe. Estimates predict there will be over 700 million speakers by 2050 due to growth primarily in Africa.

Currently, 88 countries and territories across five continents use French to communicate in their own unique way. French is the sole official language for 22 nations, a co-official language for 17, a non-official language for 22, and a working language for three.

Some of the most unexpected places we see French used today are the American state of Maine, where it remains prominent in education and the judicial branch, and Italy’s Aosta Valley, where it was taught in schools as early as the 17th century. Other surprising locales include Laos and Cambodia, which were part of French Indochina in the late 19th and early 20th centuries. These examples provide a peak into how French can be a language of power, memory, and identity — even in places where it’s not the majority tongue today.

French in the Language Services Industry

While French translation and interpreting services are commonly offered in the language industry, the current market doesn’t always provide adequate resources for all of the many unique hotspots where French is used. This can lead consumers and investors to believe that the most well-known French-speaking nations contain the greatest percentage of speakers, which is not always the case. This ultimately affects the types of French language services that are made available for these diverse communities.

When reviewing over 30 G20 market nations within the language industry for the 2022-2032 decade, the research organization Fact.MR found that French consistently ranks within the top five most-requested languages for multiple sector domains, such as diplomacy, legal affairs, and development work. Global demand for interpreters is expected to grow by 18 percent by 2031, with French dominating high-stakes, high-context environments where nuance and cultural fluency are everything.

To ensure every consumer who speaks a form of French has equal access to professional language services, being mindful of the cultures, histories, and social dynamics unique to each region should be prioritized. This includes localized vocabulary through recognition of phonetic and lexical influences to help mitigate the risk of misinterpretation.

All About the United States Office of Language Services

By

Sydnee Cooper

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July 1, 2025

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United States Office of Language Services

As the world becomes increasingly interconnected, language has never played a more critical role within global affairs. To maintain not only global peace, but also the global economy and international safety, effective multilingual communication is vital.

For the United States (US), successful international relations depend on accurate, high-quality, and professional language services. That’s where the US Department of State’s Office of Language Services (OLS) comes in.

Founded in 1789 by Thomas Jefferson, OLS functions under the Bureau of Administration and serves as the ears, voice, and words of the federal government in over 40 languages. With a mission to enable the country to carry out foreign affairs and diplomacy initiatives across the globe through the elimination of linguistic barriers, the office provides both interpreting and translation services for high-level diplomatic meetings, international summits, and official communications.

The OLS team consists of highly selective positions that require qualified candidates to undergo rigorous vetting processes. This includes career linguists who are experts in diplomacy, law, and international relations; project managers; approximately 10 to 20 direct-hire diplomatic interpreters and translators; and an additional roster of contractors for smaller languages and surge capacity. The direct-hire team works with staff project managers and hundreds of carefully tested and vetted independent-contract linguists. Services such as simultaneous and consecutive interpreting are generally provided for treaty negotiations, United Nations General Assembly sessions, and bilateral meetings with heads of state.

While OLS holds a prominent role within US government affairs, its inner workings are mostly kept private due to its work involving classified and sensitive content. However, private citizens may access a library of declassified OLS topics through the Freedom of Information Act (FOIA), allowing people to better understand things like interpreting assignments for bilateral summits, different types of translation protocols, and even budgetary and contractor usage reports. If there is specific information that a citizen or journalist may need that is not publicly available, the person has the right to send a FOIA request free of charge, which requires a response within 20 days. This process shows how OLS is able to balance integrity of its diplomatic services and its duty to serve the American public.

Walmart’s Real-Time Translation Tool Breaks Language Barriers for 1.5 Million Associates

By

MultiLingual Staff

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July 1, 2025

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Enhancing multilingual communication with AI-powered technology

Walmart has unveiled a new suite of AI tools designed to empower its 1.5 million U.S. store associates, and at the center of this rollout is a real-time translation feature available in 44 languages. The tool aims to simplify multilingual communication in the workplace, improving both associate collaboration and customer service across its nationwide footprint.

A practical solution for everyday conversations

Integrated into the Walmart associate app, the translation feature supports both text-to-text and speech-to-speech conversations. Associates can now navigate interactions with coworkers and customers in multiple languages with improved accuracy and speed.

Crucially, the system is enhanced with Walmart-specific terminology. For instance, when a customer asks, “Where’s Great Value Orange Juice?”, the tool recognizes “Great Value” as a house brand, preserving meaning across languages. The inclusion of retail-specific vocabulary reflects a key shift in real-time translation: moving beyond general phrases to context-aware communication.

Built for scale and fine-tuned with feedback

The translation system uses iterative feedback loops to improve performance over time, learning from real-world use to deliver more reliable, contextually appropriate responses. According to Walmart, additional languages and international expansion are on the roadmap, signaling a long-term investment in AI-fueled language inclusion.

AI meets frontline reality

As companies increasingly adopt AI for backend efficiencies, Walmart’s move to embed language tools in the hands of frontline staff stands out. It illustrates how large-scale employers can bridge communication gaps in linguistically diverse teams, without requiring extra hardware or apps.

For global retailers and localization professionals alike, the implications are significant. Real-time translation, when built with domain-specific intelligence and used at scale, can directly enhance operational efficiency and customer satisfaction. Walmart’s integration of language technology into everyday operations highlights a broader industry trend: using AI not just for automation, but as a tool for inclusion, communication, and practical problem-solving at scale.

John Snow Labs Launches Martlet.ai, Setting New Standards for Risk Adjustment with Healthcare Large Language Models

By

MultiLingual Staff

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July 1, 2025

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John Snow Labs, the AI for healthcare company, today announced the launch of Martlet.ai, a healthcare AI company focused on redefining how payers and providers approach Hierarchical Condition Category (HCC) Coding. Founded by engineers and payment experts from John Snow Labs, this is the first of several planned spinoff companies that will address specific, high-impact healthcare industry challenges with AI.

HCC coding plays a vital role in patient risk adjustment, directly influencing reimbursement structures and ensuring the financial sustainability of value-based care models. This is becoming even more crucial in light of the CMS Medicare Advantage rate hikes announced for 2026, which will further tie reimbursement to precise documentation and coding.

Martlet.ai’s state-of-the-art HCC engine is the answer to this challenge. Co-founded by CTO Hasham Ul Haq and CRO Ritwik Jain, this venture was born from years of hands-on success delivering AI solutions to leading healthcare enterprises. Run fully behind the customers’ firewalls, models are trained directly on patient charts to deliver unmatched accuracy, auditability, and speed. Unlike general-purpose AI tools, Martlet.ai was built for clinical documentation, making it highly effective for powering coding workflows.

West Virginia University (WVU) Medicine is already realizing the value of Martlet.ai to uncover missed HCC codes, improve risk adjustment factor (RAF) scoring, and streamline physician workflows. The implementation includes seamless two-way integration into the electronic health record (EHR) system with full compliance. As shared in their NLP Summit session “Maximizing Patient Care through AI-Enhanced HCC Code Discovery,” WVU experienced a notable increase in HCC code accuracy and a significant reduction in manual review time.

“Martlet.ai gives healthcare organizations the power to take HCC coding into their own hands with a level of customization and compliance that is unmatched,” said David Talby, CEO, John Snow Labs. “The combination of state-of-the-art, healthcare-specific, proprietary medical language models, an optimized human-in-the-loop workflow, and enterprise-grade validation layers, Martlet.ai was engineered by industry leaders to be compliant, effective, and production-ready from day one.”

To learn more or schedule a demo, visit Martlet.ai.

About John Snow Labs

John Snow Labs, the AI for healthcare company, provides state-of-the-art software, models, and data to help healthcare and life science organizations put AI to good use. Developer of Medical LLMs, Healthcare NLP, Spark NLP, the Generative AI Lab No-Code Platform, and the Medical Chatbot, John Snow Labs’ award-winning medical AI software powers the world’s leading pharmaceuticals, academic medical centers, and health technology companies. Creator and host of The NLP Summit, the company is committed to further educating and advancing the global AI community.

About Martlet.ai

Martlet.ai is an AI platform created to automate Hierarchical Condition Category (HCC) coding and streamline risk-adjustment workflows for high-compliance environments. Medicare Advantage and Medicaid MCOs, commercial insurers, ACOs, provider organizations, and revenue-cycle management (RCM) firms trust Martlet.ai for its secure, on-premise coding engine, ensuring accuracy, auditability, and transparency at every step. Made possible with domain-specific LLMs, Martlet.ai optimizes reimbursement while maintaining regulatory alignment.