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Any organization with an IT team that consists of more than a few people faces the same question with virtually every new digital project: "Should we build, or buy?".

It's a ligitimate dilemma, with customization and IP assets on one side being weighed against lower cost and faster time-to-market on the other. That said, once SalesForce kicked off the era of SaaS applications 20 years ago, the decision has increasingly been "buy".

But when it comes to AI/ML projects, for all but the very largest organizations, the "build vs. buy" question has not traditionally been up for much debate. This is because the sheer volume of data required to undertake algorithmic training has been primarily the reserve of governments, universities, global finanacial institutions, and a handful of tech giants (who generally license parts of their AI/ML tech to startups and research teams). Furthermore, the high salaries and relative dearth of data science and data modelling talent has created real barriers to self-build AI project.

But what if someone else could build your AI/ML solution, similar to how thousands of organizations outsourced their websites and mobile apps to specialist agencies and "dev shops"?

Ask AI podcast host Melissa Kargiannakis sat down with Matthew Reyes, Co-founder, Hypotenuse Labs, and asked the question: How does an AI consultancy work?

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