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#249 How to Expand in AI Data Services with DATAmundi CEO Véronique Özkaya
Manage episode 480917991 series 2975363
Véronique Özkaya, Co-CEO of DATAmundi, returns to SlatorPod for round 2 to talk about the company’s strategic rebrand and how it is positioning itself as a key player in the data-for-AI space.
Véronique details her journey to leading DATAmundi, formerly known as Summa Linguae, where she now drives a strategic shift from traditional language services to AI-focused data enablement.
The Co-CEO explains that their LSP background makes them well-suited to offer fine-tuning services for AI, especially in multilingual and domain-specific contexts. However, she cautions that language expertise alone isn’t enough; deep tech infrastructure, data science capabilities, and the ability to quickly build custom workflows are also essential.
While many companies still rely on crowd-sourced, basic annotation, DATAmundi targets higher-complexity projects requiring domain experts and linguists. Véronique notes the market for data-for-AI is growing significantly faster than traditional LSP work and sees a second wave of demand from enterprises needing to adapt pre-trained models.
Véronique highlights data scarcity, hallucination, and bias as core AI challenges that DATAmundi tackles through technical solutions and expert guidance, helping enterprises as they face pressure to implement AI despite legacy systems and unclear strategies.
Looking ahead, DATAmundi plans to expand its consultative services through further acquisitions, focusing not on tech per se, but on organizations that deepen its expertise in data application and AI deployment.
Chapters
1. Intro (00:00:00)
2. Update Since Last Podcast (00:01:03)
3. Summa Linguae History and Rebranding to DATAmundi (00:02:28)
4. Expanding Into Data-for-AI (00:07:39)
5. Strategic Acquisitions (00:10:34)
6. State of the Market in Data-for-AI (00:13:07)
7. Managing SMEs (00:17:56)
8. Competitive Landscape (00:20:35)
9. Resilience Against AI Disruption (00:23:01)
10. Tech Integration (00:27:05)
11. Distinguishing Between Automation and AI (00:31:43)
12. Future M&A Strategy (00:33:21)
13. Roadmap for 2025 (00:35:13)
249 episodes
Manage episode 480917991 series 2975363
Véronique Özkaya, Co-CEO of DATAmundi, returns to SlatorPod for round 2 to talk about the company’s strategic rebrand and how it is positioning itself as a key player in the data-for-AI space.
Véronique details her journey to leading DATAmundi, formerly known as Summa Linguae, where she now drives a strategic shift from traditional language services to AI-focused data enablement.
The Co-CEO explains that their LSP background makes them well-suited to offer fine-tuning services for AI, especially in multilingual and domain-specific contexts. However, she cautions that language expertise alone isn’t enough; deep tech infrastructure, data science capabilities, and the ability to quickly build custom workflows are also essential.
While many companies still rely on crowd-sourced, basic annotation, DATAmundi targets higher-complexity projects requiring domain experts and linguists. Véronique notes the market for data-for-AI is growing significantly faster than traditional LSP work and sees a second wave of demand from enterprises needing to adapt pre-trained models.
Véronique highlights data scarcity, hallucination, and bias as core AI challenges that DATAmundi tackles through technical solutions and expert guidance, helping enterprises as they face pressure to implement AI despite legacy systems and unclear strategies.
Looking ahead, DATAmundi plans to expand its consultative services through further acquisitions, focusing not on tech per se, but on organizations that deepen its expertise in data application and AI deployment.
Chapters
1. Intro (00:00:00)
2. Update Since Last Podcast (00:01:03)
3. Summa Linguae History and Rebranding to DATAmundi (00:02:28)
4. Expanding Into Data-for-AI (00:07:39)
5. Strategic Acquisitions (00:10:34)
6. State of the Market in Data-for-AI (00:13:07)
7. Managing SMEs (00:17:56)
8. Competitive Landscape (00:20:35)
9. Resilience Against AI Disruption (00:23:01)
10. Tech Integration (00:27:05)
11. Distinguishing Between Automation and AI (00:31:43)
12. Future M&A Strategy (00:33:21)
13. Roadmap for 2025 (00:35:13)
249 episodes
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