How we found our product-market fit
Getting the product-market fit completely right with Osterus was a tough one, let me explain why and I acknowledge we might not be 100% there yet….but we are definitely on the right path.
Right from the get go, we wanted to make sure recruiters would never miss out on qualified talent because they couldn’t understand an unfamiliar CV. Knowledge is power. Knowledge used to understand positive data signals could be exceptionally powerful. Our ambition and vision grew over time when we saw how much more you can do with data signals in a CV than we ever thought.
This is the journey we’ve had so far but I’ll start from the beginning.
1) We started by building a CV processing tool, which can extract data points from CVs, learn and understand patterns around career trajectories, education, companies’ preferences, the importance of degrees, subjects, cost of living, quality of life and other factors.
Gilad (my co-founder) built a system that obfuscated personal information, removing the name, contact details, and obvious links on a CV which could lead you to the public profile of an individual. We initially did this to add another layer of security for GDPR purposes, but straight away recruiters and H.R. personnel pointed out that they would love to use this as an anti-bias tool.
2) We then decided to push boundaries a little further and started working on the technology to sort CVs based on the probability of a person succeeding within a specific company. We do this by looking at similarities between companies and their recruitment process, ratings of employees and multiple factors around industry, current workforce and their statistics. Having said that, we never make the final decision. We just create different groups of CVs, where we believe they match the preferred criteria of the recruiters and then show the likelihood of a good match between each set.
3) Our understanding of CVs and the correlation of data points to the likelihood of individual employee success has become advanced. So much so that investors such as VCs, PE’s and M&A departments want to use our software to understand the capacity and skill set of the human capital and compare it with the competition.
There are many more options, there is even the potential to use someone’s CV to make predictions on their credit score or career trajectory.
Now we have the luxury problem of choosing our domain and dominating it.
We paid close attention to the market. We know, if we are going to be serious about reducing bias and enriching data beyond the current tools on the market we have to start with recruitment. This means giving companies the capabilities to understand bias and give them the tools to start recruiting in a data-driven way without looking at gender or nationality, for example.
Once we have mastered this domain, rest assured, we will build out more powerful tools. We will help the historically disenfranchised, immigrants and make sure people can learn what skills and capabilities can put them on the desired career path.
At Osterus we have a saying, “let the data speak”. We will give companies the necessary tools to hire in a data-driven way. This will ensure that talent across the globe can apply to any job and have a good chance to be considered. Osterus will create borderless opportunities and drive diversity.
