FiddleCube generates high-quality safety datasets for training and red-teaming large language models (LLMs), ensuring compliance with AI security standards such as OWASP and NIST. The platform addresses the need for effective data management and continuous feedback to mitigate vulnerabilities and enhance model alignment.
Funding
$500K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Large language models (LLMs) are vulnerable to various safety and security risks, including adversarial attacks, data leakage, and the generation of harmful content. Existing methods for mitigating these risks often lack comprehensive, high-quality datasets for training and red-teaming. This makes it difficult to ensure LLMs adhere to AI safety standards and ethical guidelines.
Solution
FiddleCube provides safety datasets designed to train and red-team LLMs, addressing critical vulnerabilities and enhancing model alignment. The platform enables data management and continuous feedback to mitigate risks during pre-training, fine-tuning, and reinforcement learning with human feedback (RLHF). FiddleCube helps organizations comply with AI security standards such as OWASP, NIST, and MITRE by identifying and mitigating critical vulnerabilities. The datasets can be hosted privately, ensuring data privacy and preventing data from being used for further AI training.
Target Audience
FiddleCube is designed for enterprises and AI developers building and deploying LLMs who need to ensure AI safety, comply with industry standards, and protect against vulnerabilities.
Features
- Datasets designed for safety during pre-training, fine-tuning, and RLHF
- Red-teaming and reinforcement learning datasets to test model alignment and helpfulness
- Continuous feedback mechanisms to detect and mitigate new attacks
- Private hosting options to ensure data privacy and prevent data leakage
- Compliance with AI security standards, including OWASP, NIST, and MITRE