AI Assurance Platform, Raises $4.5 Million In Seed Funding

AI Assurance Platform Raises $4.5 Million In Seed Funding

by NeoTech Post, an AI Assurance platform, secured $4.5 million in seed funding, led by Capri Ventures and F2 Capital. 

According to a recent IBM report, 78% of business leaders said that trusting the fairness, safety, and reliability of AI outputs is very important. 

However, AI in production is a black box, making it difficult for models to be continuously monitored and maintained for accuracy and fairness. Inaccuracies can be introduced into AI models due to changes in the data that feeds them, market preferences, product updates, or marketing efforts. 

Errors by the model can result in lost profits, cybersecurity breaches, or, in the worst cases, for industries like healthcare, even loss of life. Most businesses lack the tools and practices to effectively detect and prevent inaccuracies from being introduced, making AI models’ scalability impossible.

“Business leaders are eager to implement and reap the benefits of AI, but quickly discover that complexity and lack of visibility create serious trust issues once in production,” said Ofer Razon, co-founder and CEO of 

“Most organizations don’t discover issues with their model until it’s too late, and there’s already a negative business impact. This is partly caused by the fact that in most cases, it’s not even clear who within an organization owns the long term health and accuracy of AI models. Our team has years of experience dealing with this problem across dozens of enterprises, putting us in a unique position to guide our data-driven customers and give them trust in their models.”

The platform includes AI performance management, bias detection, explainability, and AI analytics capabilities. It gives business and operational teams a direct view of what’s happening in their AI models and why and offers proactive actions and recommendations to optimize the model’s behavior for better performance and outcomes. 

The platform helps protect businesses from the harmful, unintended consequences of biased AI models. By handling issues in real-time, the platform allows the business and operational teams to own the ongoing performance of the models, reducing their dependency on the data science team who can then focus on new initiatives. 

The AI Assurance platform integrates seamlessly into whatever AI platform is already in use, including AWS SageMaker, Google AI Platform, Azure Machine Learning, Kubeflow,, and custom-built platforms. 

According to the company, its platform is being used by several customers, who can now detect and solve any issues in their AI models in real-time, revolutionizing the current reactionary approach that’s triggered by dropped business KPIs, which only occur after an error has become an issue.

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