Turning Data Into Direction with Veronique Ozkaya

Turning Data Into Direction with Veronique Ozkaya

Introduction to Veronique Oscaya

  • Introduction of Veronique Oscaya, co-CEO at datamundi.ai with over 25 years in the industry.
  • Discussion on the transformation from Sumalingua Technologies to datamundi.ai to meet market demands.
  • Fun fact about Izmir: birthplace of Aristotle Onassis and home to the ancient city of Ephesus.

Company Evolution and Strategy

  • Overview of Sumalingua's transition to focus on data services.
  • Acquisition history: GlobalMe in 2019 for audio collection services; Damundi in 2020 for data services.
  • Importance of enhancing and cleaning data sets for business purposes.

Future Directions and AI Integration

  • Historical context: evolution from CAT tools to neural MT, leading up to AI advancements with GPT.
  • Rationale behind joining datamundi.ai due to its future-oriented vision in data services.
  • Emphasis on multilingual capabilities as a competitive advantage in AI development.

Rebranding and Client Focus

  • Decision to rebrand as datamundi reflecting their expanded focus on global data services.
  • Clients often overlook the value of their multilingual data beyond translation tasks.

The Evolving Role of Localization in AI Initiatives

  • Organizations are seeking strategic multilingual data ownership to meet new localization needs.
  • Localization managers must ensure AI assistants cater to diverse language requirements across global teams.
  • Companies need to leverage data insights for sales improvement, enhancing product descriptions based on customer feedback.

Importance of Quality Data in AI Systems

  • Enhancing product descriptions can significantly boost sales through better alignment with client goals.
  • Effective AI systems rely on high-quality data; poor data leads to inaccuracies and biases in responses.
  • Addressing issues like incomplete or biased data is crucial for improving AI assistant performance.

Client Collaboration and Data Improvement Strategies

  • Clients often request assistance in collecting and refining data sets for better system integration.
  • Iterative improvements in data quality lead to enhanced user satisfaction and productivity with AI tools.

Internal Transformation at Datamundi

  • Datamundi's rebranding reflects a strategic pivot towards transparency and clarity in operations.
  • Training programs have been implemented for sales teams to understand services and market opportunities better.

Adapting Operations for Evolving Client Needs

  • Significant restructuring has occurred within the company, particularly shifting resources into the data unit.

Understanding the Importance of Innovation and Data Quality

Key Insights on Innovation and Team Alignment

  • Emphasizes the need for innovation and alignment among sales, tech teams, and talent pools.
  • Highlights the importance of high-quality data and specialized skills in data services.
  • Discusses challenges in curating supply chains for data services.

Case Studies Demonstrating Effective Data Use

  • Mentions case studies showcasing agility, efficiency, scalability, and speed in client services.
  • Describes a project during presidential elections that provided real-time news updates across countries.
  • Talks about chatbots created to reduce live call center interactions by directing queries effectively.

Addressing Bias in Language Data

  • Explains the measurement of chatbot effectiveness based on user engagement without agent involvement.
  • Discusses cleaning biased datasets to ensure fair representation in language processing tasks.
  • Notes the variety of problems faced by project managers due to evolving client needs.

The Role of Multilingualism in AI Applications

  • Highlights specialization in high-quality data while addressing diverse client requirements.
  • Stresses the critical role of multilingualism as AI expands globally beyond English-centric applications.

The Importance of Multilingualism in AI Adoption

Understanding Language in AI

  • Comfort in using one's own language is crucial for AI adoption as it becomes more widespread.
  • Basic tasks are highly automated, emphasizing the need for multilingual knowledge to understand system functions.

Evolving Client Needs

  • Initial client needs were basic and volume-focused; now they demand more complexity and quality.
  • Data tasks have evolved from simple categorization to complex requirements due to rapid advancements in AI systems.

Specialization and Validation

  • Systems must validate diagnostics accurately, requiring specialized professionals to ensure data correctness.
  • Internal processes must be established for effective resource sourcing and data validation.

Consulting vs. Providing Services

  • Being a partner means understanding client goals beyond just providing data services.

Consultative Selling and Process Improvements

  • Discusses building a tool for annotators to enhance product descriptions by simulating the client's environment.
  • Highlights the importance of communicating limitations in data improvements to clients, fostering transparency.
  • Emphasizes consultative selling as crucial for client relationships and future business growth.

Core Values at Datamundi

  • Identifies three main values: open-mindedness, resilience, and transparency, essential for organizational success.
  • Open-mindedness encourages innovation; resilience helps teams overcome challenges without complaint.
  • Transparency builds trust with clients by clearly communicating strategies and execution plans.

Future Trends in Technology

  • Predicts further disruption due to technology, which may initially seem daunting but can lead to efficiency gains.
  • Acknowledges that technological changes will be significant but beneficial for client operations.
  • Notes the rapid growth of AI services as a vibrant market with opportunities for specialized skills.

Final Thoughts on Embracing Technology

  • Encourages embracing technology and maintaining an open mind to discover new paths forward.

The Future of the Language Services Industry

Industry Evolution

  • The global language services industry is expected to evolve dramatically in the coming years.
  • Embracing changes in the industry will allow participants to be part of its success.
Channel: MultiLingual
Video description

In this episode, we speak with Veronique Ozkaya, Co-CEO of Datamundi AI, about the company’s transformation from Summa Linguae Technologies into a data-focused, AI-driven service provider. Drawing on her 25+ years in the language industry, Veronique explores how multilingual data is becoming central to enterprise AI strategies—and why localization teams are well positioned to lead this shift. We discuss the rebranding decision, the evolution of data services, real client use cases, and the internal cultural changes required to support such a pivot. Veronique also reflects on the strategic role of language in AI adoption, the challenges of bias and data quality, and the core values—openness, resilience, and transparency—that drive Datamundi’s vision for the future.