"White Circle , a platform that helps companies monitor, secure and control AI models in production, has raised $11m in Seed funding, the company announced today. The capital will fund product development and hiring across the US, UK and Europe. The round features personal investments from a notable list of AI-industry figures: Romain Huet (OpenAI); Dirk Kingma (formerly OpenAI, now at Anthropic); Guillaume Lample (Mistral); Thomas Wolf (Hugging Face); Olivier Pomel (Datadog); François Chollet (creator of Keras); Mehdi Ghissassi (formerly DeepMind); Paige Bailey (DeepMind); and David Cramer (Sentry)."
"The participation list reads as senior practitioners from the labs that build the models White Circle is designed to police. White Circle was founded by engineer Denis Shilov, who went viral in 2024 after a single prompt bypassed the safety filters of every major AI model. The post reached 1.4 million views, prompted contact from Anthropic, OpenAI and Hugging Face, and led to Shilov joining Anthropic's bug-bounty programme. The White Circle platform was built to address the gap his demonstration exposed."
"The product is a single-API control layer that scans AI inputs and outputs in real time against customer-defined policies. It detects harmful content, catches hallucinations, blocks prompt-injection attacks, flags model drift and identifies abusive users. Customers can set custom enforcement actions, including rate-limiting and bans, and feed labelled user feedback back into White Circle's models to improve accuracy over"
White Circle, a platform for monitoring, securing, and controlling AI models in production, raised $11m in Seed funding. The funding will support product development and hiring across the US, UK, and Europe. The round includes personal investments from senior AI-industry figures associated with OpenAI, Anthropic, DeepMind, Hugging Face, Mistral, Datadog, Sentry, and Keras. White Circle’s platform provides a single-API control layer that scans AI inputs and outputs in real time against customer-defined policies. It detects harmful content, catches hallucinations, blocks prompt-injection attacks, flags model drift, and identifies abusive users. Customers can apply custom enforcement actions such as rate-limiting and bans and use labeled user feedback to improve model accuracy.
Read at TNW | Investors-Funding
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