To apply AI insights to software engineering, Faros AI raises $20 million

Software engineering-focused artificial intelligence (AI) firm Faros AI has secured $20 million in series A investment, which was headed by Lobby Capital and included SignalFire, Operator Collective, and Salesforce Ventures. With the money, Faros AI will be able to expand its engineering intelligence platform, which intends to provide company executives with insights into their software development procedures.

Vitaly Gordon, co-founder and CEO of Faros AI, said in an interview with VentureBeat that the financing comes at a time when demand for the company\’s services is increasing amid a larger drive for productivity and efficiency. The recent market collapse has caused an increase in the number of businesses putting an emphasis on productivity and efficiency, according to Gordon.

The platform developed by Faros AI incorporates data from a variety of software development platforms, including source code repositories like GitHub and project management systems like Jira, to provide what it refers to as \”multilateral visibility\” into engineering activities. The corporation claims that despite software becoming more complicated, information about how it is created has remained compartmentalised across several systems, making it difficult for managers to improve their procedures.

Engineering executives were previously not really questioned and not really held responsible for how they utilised pricey resources, but Gordon suggested that things were about to change. When businesses begin to provide such metrics to their board and C-suite, a tipping point will occur. More people will want responsibility and visibility.

Building an engineering \”system of record\”

Faros AI was established in 2020 by three ex-Salesforce executives who created the Einstein machine learning platform with the goal of giving engineering leaders better visibility and understanding into their processes and performance.

Gordon claims that the startup was at least partly motivated by his time spent as a vice president of engineering at Salesforce, when he saw that the performance and operations of engineering executives lacked data-driven insights. Additionally, he said that Faros AI sets itself apart from competing AI and software engineering solutions by offering a layer of insight across the many platforms and processes that engineering organisations use.

Gordon said, \”We\’re not replacing any of the technologies that I mentioned, including Jira, Github, and CI/CD systems. We are only an extra layer that contributes to better tool visibility.

Using everyday language for analysing data

Additionally, Gordon said that the business intends to introduce Lighthouse AI, an artificial intelligence engine, in the first part of 2023 Q3. Users will be able to acquire information regarding engineering operations from various systems using Lighthouse AI, which will also allow for the use of natural language for exploratory data analysis and, ultimately, guided AI-driven navigation.

In the next five years, AI will completely revolutionise software engineering, according to Gordon. And we are developing the infrastructure that will enable software companies to successfully make that move.

Faros AI already has partnerships with some of the top businesses in the industrial, retail, financial services, and technology industries. Salesforce, Autodesk, Coursera, and Box are a few of its clients. By identifying and resolving the bottlenecks in their engineering processes, the business claimed to have assisted its clients in enhancing their feature velocity, cutting costs, and maximising resources.

\”If you look at some of the most successful SaaS companies of our time, they are the single source of truth for a system of record for a specific function: Salesforce is sales; ServiceNow is IT; and Workday is HR and finance,\” said Gordon. \”Engineering as a function is bigger than all of the other functions put together. As the one source of truth for all of that data, we think that the potential to solve that technical challenge is very significant.

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