For venture capitalists, assessing the ML maturity of their potential investment deserves special attention. Slingshot Ventures fully acknowledged this, and they used the Enjins ML audit for their investment decision concerning Fintech lender Swishfund.

The explosion of ‘AI-First’ companies raises questions like;

• How mature are the ML capabilities of tech scale-ups and start-ups?
• Is the underlying ML infrastructure scalable for its growth?
• Are Human Assets (Data Scientists and Engineers) ready for the new step?
• Are data pipelines and algorithms dynamic to a changing world?

These questions are becoming extremely relevant for investment funds when deciding about a potential tech investment. However, these questions are currently not included in an IT due diligence. The ML assets are often a blind spot for investors.That is why Enjins developed the ML Audit.

The Enjins Machine Learning Audit is a two day on-site review. Through interviews, architecture reviews and assessments on existing ML algorithms we assess the current ML maturity level and the ML scalability. In a company’s early stage of data science and machine learning, ad-hoc and partly manual solutions might be sufficient to test the companies ideas and business models. However, when businesses scale, these ad-hoc solutions will no longer be sufficient and will fail one way or the other. Therefore, timely assessing the machine learning infrastructure is key to secure future success.

The ML audit assesses the capabilities from a technical and business perspective. From a technical perspective, the data quality, infrastructure, algorithms and data completeness are reviewed. The data completeness check gives actionable advice on events which are currently not logged. Starting with this today, means the data will actually be available when building the use case one or two years from now.

From a business perspective, the future value and costs of ML for the company is assessed. What are the most important use cases? What will be the future costs when further scaling the infrastructure? And which additional assets in terms of human resources are needed?
The technical and business review together are delivered in the ML audit report.

In August, Enjins executed the ML audit for Slingshot Ventures during their assessment of Fintech Lender Swishfund. The transaction was announced last week. Enjins also regularly executes ML audits commissioned by the company. For entrepreneurs, the audit brings an additional pair of eyes for created ML algorithms and a thorough challenge of the companies ML roadmap.

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