About
Laconic
Laconic means to the point.
Laconic Ltd. is a single-person AI advisory and consultancy company founded by Oguzhan Gencoglu in 2022. It is located in Helsinki, Finland and operates globally. Our clients vary from early stage start-ups to large corporations.
Me
Hi! I am Oguzhan (Ouz) Gencoglu, a Machine Learning and Decision Science expert. I consider myself cheerful, factual, and curious.
I take a holistic view to Machine Learning:
Science & Tech
- Deep tech expertise | 10+ years in Machine Learning & AI
- Profound understanding of scalable AI development and productionizing | delivered 60+ AI solutions ranging from Computer Vision to Natural Language Processing in various industries
- Several peer-reviewed scientific publications on machine learning
Business & Strategy
- Previously co-founded Top Data Science in 2016 - an AI consultancy from Finland. Grew the business and the team as Head of AI, steered the company strategy as a board member which resulted in an acquisition by Morpho Inc.⧉ from Japan (listed in Tokyo stock exchange) partially in 2018 and fully in 2021
- Nowadays building an evaluation platform for LLM applications at Root Signals AI⧉
- Serving as an external advisor or board member in different companies
Leadership, Mentoring & Community
- Mentor and supervisor to my teams
- Peer reviewer to scientific publications, contribution to open source @ GitHub⧉
- Avid speaker with appearances @ MLOps Community⧉, CVPR⧉, PyData⧉, Finnish Center for AI⧉, MyData⧉. Given ~100 talks, workshops, and trainings on machine learning. Some of my podcast appearances at Spotify:
Policymaking
- I advise OECD on AI policymaking
Articles
My articles aim to serve as live documents that are updated whenever necessary rather then static runestones. I try to keep my articles to-the-point by spending significant time to make them shorter. Quality is prioritized over quantity. As I am willing to update my analyses or views when presented with new data, I would appreciate corrections, suggestions, or general comments.
Each article has a topical tag (e.g. Machine Learning⧉). External links⧉, tooltips (hover mouse or click)◥ and citations [1, 2] follow these formats.