FAQ

The word Kavout comes from regional French and means “to find.” At Kavout, we are explorers of new territories that few have set foot on before.

We serve the investment community and companies like hedge funds, institutional asset managers, portfolio and fund managers, Registered Investment Advisors, data buyers and distributors, quant funds, proprietary trading firms, and risk management firms.

Our technology is built upon a variety of state-of-the-art machine learning models, including deep learning and Bayesian probabilistic models. Even though Kavout is using advanced models, our philosophy is still driven by core financial principles. Every factor and model Kavout build has an underlying financial thesis.

Kavout’s solutions and services can help you:

• Augment your team’s human intelligence with AI
• It enables you to service more customers and increase asset under management (AUM) by using new technologies.
• Increases your competitiveness and the ability to stay current on the latest solutions.
• Generate actionable insights from a sea of data. Kavout support our customers to separate signals from noise.
• Mitigate risks and reduce downside based on actionable insights.
• Increase operational efficiency while keeping cost-to-income ratio low

Below are a few of the ways these types of models differ.

• Capacity to learn: While traditional statistical models are static, machine learning-based models learn, adapt and improve their methods as they process new inputs.
• Number of variables: Traditional statistical models are only able to address a limited number of variables. Meanwhile, machine learning models can address thousands, even millions of variables thanks for advancement in computing power.
• Forgiveness to noisy data: Machine learning models are able to extract meaningful insights from noisy, unstructured data like social media, news, blogs while traditional statistical models simply cannot handle this.

Kavout’s solutions and services can help you:
We have assembled a world-class data science, engineering, and finance team to research and build our platform. Our team come from backgrounds in AI, machine learning, big data, and quantitative financial analysis, with decades of professional work experience in high tech and quantitative finance companies like Google, Microsoft, Thompson Reuters, Baidu, and other Wall Street institutions. This combination makes Kavout uniquely qualified to help you integrate new and scalable technologies into the processes of your investment firm. Visit the Who We Are page to learn more.

Contact us if you are interested in purchasing our products. In addition, Kai as a Service (KaaS) is a service platform that you can subscribe to and leverage our pre-built models and algorithms.

Client confidentiality and data privacy are of the utmost importance to us. All Kavout team members who work on a project sign confidentiality agreement with our clients to ensure their information is protected. In addition, all client data is stored on secure servers. We also use a login encryption process for particularly sensitive data items.

Our technology is built upon a variety of state-of-the-art machine learning models, including deep learning and Bayesian probabilistic models. Even though Kavout is using advanced models, our philosophy is still driven by core financial principles. Every factor and model Kavout build has an underlying financial thesis.

Machine learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to learn from data, without being explicitly programmed.

Not at all. At Kavout, we create AI and ML solutions to augment human intelligence. Because of its capacity to process large amounts of data at scale, there are some things that AI solutions are better at. Meanwhile, humans are better at higher-level strategic thinking. We believe in a hybrid model where AI solutions can support and empower humans by providing them with the information they need to make strategic decisions.