Total raised: $57.65M
Funding Rounds 2
| Date | Series | Amount | Investors |
| 08.05.2024 | - | $46M | - |
| 22.02.2024 | - | $11.65M | - |
Mentions in press and media 5
| Date | Title | Description |
| 08.05.2024 | DatologyAI raises $46M to streamline AI model training data diets Your vote of support is important to us and it helps us keep the content FREE. One click below supports our mission to provide free, d... | Artificial intelligence data curation startup DatologyAI said today it has closed on a $46 million early-stage round of funding, which comes just three months after it first announced it had raised $11.65 million in seed funding. The compan... |
| 03.04.2024 | WSJ: OpenAI рассматривает возможность использования транскрипций с YouTube для обучения GPT-5 | OpenAI рассматривает возможность обучения своей следующей модели искусственного интеллекта GPT-5 на транскрипциях роликов с YouTube, сообщила Wall Street Journal со ссылкой на источники. Таким образом компании в сфере ИИ ищут неиспользованн... |
| 22.02.2024 | DatologyAI raises $11.65M to automate data curation for more efficient AI training Your vote of support is important to us and it helps us keep the content FREE. One click below supports our mission t... | Datology AI, a data curation startup that aims to make it easier to build the enormous training datasets required by generative artificial intelligence models, said today it has closed on an $11.65 million seed funding round. The round was ... |
| 22.02.2024 | DatologyAI is building tech to automatically curate AI training datasets | Massive training datasets are the gateway to powerful AI models — but often, also those models’ downfall. Biases emerge from prejudicial patterns concealed in large datasets, like pictures of mostly white CEOs in an image classification set... |
| - | DatologyAI | “DatologyAI builds data curation tools to automatically select the best data on which to train GenAI models. We leverage cutting-edge research—much of which we perform ourselves—to identify redundant, noisy, or otherwise harmful data points... |