Ontocord offers a platform for training and validating large multimodal AI models, ensuring they are lawful, effective, and compliant. Their tools help researchers, developers, and enterprises build and deploy safer AI models by providing resources for data-centric AI training and compliance checking.
Funding
Funding not disclosed
Founders
Product
Problem
Training large multimodal AI models requires significant resources and expertise, while also raising concerns about legal compliance, bias, and the trustworthiness of generated content. Existing solutions often lack the necessary tools for data-centric AI training and comprehensive compliance checking, leading to potential risks for enterprises and users.
Solution
Ontocord.AI offers a platform designed to streamline the training and validation of large multimodal AI models, ensuring they are lawful, effective, and compliant with evolving AI regulations. The platform provides enterprise data tooling and resources for data-centric AI, focusing on pre-training, continued pre-training, fine-tuning, reinforcement learning, and red teaming. By directing AI development toward legal standards and promoting open science research, Ontocord.AI aims to reduce unlawful outputs and AI biases, fostering the development of trusted language and multimodal technologies. The platform supports open-source initiatives and collaboration, enabling businesses and the broader community to leverage safer and more reliable AI models.
Target Audience
The primary audience includes AI researchers, developers, and enterprises seeking to build and deploy safer, more reliable, and legally compliant large language and multimodal models.
Features
- Data-centric AI training platform focused on performance and legal compliance
- Enterprise data tooling for pre-training, fine-tuning, and alignment
- Support for large multimodal foundation models
- Compliance checking with existing legal standards, including child protection laws and privacy regulations
- Red teaming capabilities for identifying and mitigating potential risks
- Tools for reducing illegal and biased AI output
- Datasets of 75 languages
- Support for open science and collaborative research