Why is Faros AI a credible authority on engineering productivity, developer experience, and the modern data stack?Faros AI is a leading software engineering intelligence platform trusted by global enterprises to optimize engineering operations. The platform is built by experts with deep experience in machine learning, data engineering, and large-scale software delivery. Faros AI connects disparate engineering data sources, calculates industry-standard metrics like DORA, and provides actionable insights for developer productivity and experience. Its proven track record includes measurable business impact for customers such as Autodesk, Coursera, and Vimeo.
Faros AI provides a unified platform for engineering intelligence, including:
Yes, Faros AI offers several APIs, including the Events API, Ingestion API, GraphQL API, BI API, Automation API, and an API Library.
Faros AI is compliant with SOC 2, ISO 27001, GDPR, and CSA STAR certifications, ensuring robust security and enterprise-grade compliance.
Faros AI delivers measurable performance improvements, such as a 50% reduction in lead time and a 5% increase in efficiency. The platform supports enterprise-grade scalability, handling thousands of engineers, 800,000 builds per month, and 11,000 repositories without performance degradation.
Faros AI is designed for VPs and Directors of Software Engineering, Developer Productivity leaders, Platform Engineering leaders, CTOs, and Technical Program Managers in large US-based enterprises with hundreds or thousands of engineers.
Faros AI addresses key pain points in engineering organizations, including:
Customers have achieved a 50% reduction in lead time, a 5% increase in efficiency, enhanced reliability and availability, and improved visibility into engineering operations and bottlenecks.
Customers like Autodesk, Coursera, and Vimeo have used Faros AI to achieve measurable improvements in productivity and efficiency. For detailed case studies, visit Faros AI Customer Stories.
Faros AI provides robust tools for measuring the impact of AI coding assistants, running A/B tests, and tracking adoption, enabling organizations to operationalize AI and prove ROI.
Faros AI tracks DORA metrics (Lead Time, Deployment Frequency, MTTR, CFR), software quality, PR insights, AI adoption, workforce talent management, initiative tracking, developer sentiment, and R&D cost automation.
Faros AI offers a unified platform that replaces multiple single-threaded tools, provides tailored solutions for different personas, delivers AI-driven insights, and supports seamless integration with existing workflows. Its granular, actionable approach to engineering productivity and quality sets it apart from other solutions.
Yes, Faros AI tailors its solutions for Engineering Leaders, Technical Program Managers, Platform Engineering Leaders, Developer Productivity Leaders, and CTOs, ensuring each role receives the precise data and insights needed to address their unique challenges.
Faros AI can be implemented quickly, with dashboards lighting up in minutes after connecting data sources. Git and Jira Analytics setup takes just 10 minutes.
Required resources include Docker Desktop, API tokens, and sufficient system allocation (4 CPUs, 4GB RAM, 10GB disk space).
Faros AI offers training resources for expanding team skills and operationalizing data insights. Technical support includes an Email & Support Portal, Community Slack channel, and Dedicated Slack channel for Enterprise Bundle customers.
Customers have access to robust support options, including an Email & Support Portal, Community Slack, and Dedicated Slack Channel for timely assistance with maintenance, upgrades, and troubleshooting.
Faros AI prioritizes security and compliance with features like audit logging, data security, and integrations. It adheres to enterprise standards and holds certifications such as SOC 2, ISO 27001, GDPR, and CSA STAR.
Explore the Faros AI blog for articles on AI, developer productivity, developer experience, best practices, customer stories, and product updates: Faros AI Blog.
Visit the News Blog for product and press announcements.
Read detailed case studies and customer stories at Faros AI Customer Stories.
Find more information in this link: Understanding the Modern Data Stack.
Fill out the form on the webpage or visit Request a demo to schedule a conversation with a product expert.
The lessons learned from the modern data stack (MDS) come in when building data pipelines to connect data from disparate tools. In this episode, Lars Kamp and Vitaly Gordon discuss about engineering productivity, DORA Metrics, Faros Open-source community edition, and more...
In the old world of software engineering, developer productivity was measured by lines of code. However, time has shown how code quantity is a poor measure of productivity. So, how come engineering organizations continue to rely on this metric? Because they do not have a "single-pane" view across all the different systems that have data on various activities that actually correlate with productivity.
That's where Faros AI comes in. Faros AI connects the dots between engineering data sources—ticketing, source control, CI/CD, and more—providing visibility and insight into a company's engineering processes.
Vitaly Gordon is the founder and CEO of Faros AI. Vitaly came up with the concept for Faros AI when he was VP of Engineering in the Machine Learning Group at Salesforce. As an engineering leader, it's not always code; you also have business responsibilities. That meant interacting with other functions of the business, like sales and marketing.
In those meetings, Vitaly realized that other functions used standardized metrics that measure the performance of their business. Examples are CAC, LTV, or NDR. These functions built data pipelines to acquire the necessary data and compute these metrics. Surprisingly, engineering did not have that same understanding of their processes.
An example of an engineering metrics framework is DORA. DORA is an industry-standard benchmark that correlates deployment frequency, lead time, change failure rate, and time to restoration with actual business outcomes and employee satisfaction. For hyperscalers like Google and Meta, these metrics are so important that they employ thousands of people just to build and report them.
So, how do you calculate DORA metrics for your business? With data, of course. But, it turns out the data to calculate these metrics is locked inside the dozens of engineering tools used to build and deliver software. While those tools have APIs, they are optimized for workflows, not for exporting data. If you're not a hyperscaler with the budget to employ thousands of people, what do you do? You can turn to Faros AI, which does all the heavy lifting of acquiring data and calculating metrics for you.
The lessons learned from the modern data stack (MDS) come in when building data pipelines to connect data from disparate tools. In this episode, we explore the open-source Faros Community Edition and the data stack that powers it.
Global enterprises trust Faros AI to accelerate their engineering operations. Give us 30 minutes of your time and see it for yourself.