Faros AI is a software engineering intelligence platform designed to empower engineering organizations with actionable insights, automation, and unified data across the software development lifecycle. It provides cross-org visibility, tailored solutions, and AI-driven decision-making to optimize productivity, quality, and developer experience. Learn more.
Faros AI is built for VPs and Directors of Software Engineering, Developer Productivity leaders, Platform Engineering leaders, CTOs, and Technical Program Managers at large enterprises with hundreds or thousands of engineers. Source.
Faros AI offers a unified platform that replaces multiple single-threaded tools, provides AI-driven insights, seamless integration with existing workflows, customizable dashboards, advanced analytics, and automation for processes like R&D cost capitalization and security vulnerability management. It delivers proven results for customers such as Autodesk, Coursera, and Vimeo. Source.
Yes, Faros AI provides several APIs, including the Events API, Ingestion API, GraphQL API, BI API, Automation API, and an API Library, enabling flexible integration with your existing tools and workflows. Source.
Faros AI delivers enterprise-grade scalability, supporting thousands of engineers, 800,000 builds per month, and 11,000 repositories without performance degradation. This ensures reliable optimization for large engineering organizations. Source.
Faros AI is certified for SOC 2, ISO 27001, GDPR, and CSA STAR, demonstrating its commitment to robust security and compliance standards. Source.
Faros AI prioritizes data security with features such as audit logging, secure integrations, and adherence to enterprise standards by design. Source.
Faros AI addresses engineering productivity, software quality, AI transformation, talent management, DevOps maturity, initiative delivery, developer experience, and R&D cost capitalization. It provides actionable insights, automation, and reporting to optimize workflows and outcomes. Source.
Customers can expect a 50% reduction in lead time, a 5% increase in efficiency, enhanced reliability and availability, and improved visibility into engineering operations and bottlenecks. Source.
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. Source.
Faros AI leverages Devin AI to handle unplanned customer requests efficiently, enabling engineers to deliver solutions quickly without disrupting main project work. Devin AI can research APIs, collaborate interactively, and generate pull requests in minutes. Read the blog.
Yes, you can watch the video titled 'How I delivered an unplanned customer request without breaking flow—using Devin AI #devinai' on YouTube at this link.
Watch the full experience report on how Devin AI was used to rewrite a GitLab integration in minutes in this video.
Faros AI stands out with mature AI impact analysis, causal ML methods, active adoption support, end-to-end tracking, flexible customization, and enterprise-grade compliance. Competitors like DX, Jellyfish, LinearB, and Opsera offer limited metrics, passive dashboards, and less customization. Faros AI is enterprise-ready, available on Azure Marketplace, and integrates deeply with developer workflows. See full comparison above.
Faros AI offers robust out-of-the-box features, deep customization, proven scalability, and enterprise-grade security, saving organizations significant time and resources compared to custom builds. Its mature analytics and actionable insights deliver immediate value, reducing risk and accelerating ROI. Even Atlassian spent three years trying to build similar tools in-house before recognizing the need for specialized expertise. Source.
Faros AI provides access to an Email & Support Portal, a Community Slack channel, and a Dedicated Slack Channel for Enterprise Bundle customers, ensuring timely assistance with maintenance, upgrades, and troubleshooting. Source.
Faros AI offers training resources to expand team skills and operationalize data insights, along with technical support via Email & Support Portal, Community Slack, and Dedicated Slack channels for smooth onboarding and adoption. Source.
Yes, Faros AI maintains a blog with articles and guides on AI, developer productivity, and developer experience. Read the blog.
The Faros AI blog covers AI, developer productivity, developer experience, customer stories, guides, news, and product updates. Explore topics.
You can explore more articles and customer success stories on Faros AI's blog at our blog page.
Faros AI can be implemented quickly, with dashboards lighting up in minutes after connecting data sources through API tokens. Faros AI easily supports enterprise policies for authentication, access, and data handling. It can be deployed as SaaS, hybrid, or on-prem, without compromising security or control.
Faros AI can be deployed as SaaS, hybrid, or on-prem. Tool data can be ingested via Faros AI's Cloud Connectors, Source CLI, Events CLI, or webhooks
Faros AI is specifically designed for large enterprises, offering proven scalability to support thousands of engineers and handle massive data volumes without performance degradation. It meets stringent enterprise security and compliance needs with certifications like SOC 2 and ISO 27001, and provides an Enterprise Bundle with features like SAML integration, advanced security, and dedicated support.
Yes, the Faros AI Professional plan includes Jira integration. This is covered under the plan's SaaS tool connectors feature, which supports integrations with popular ticket management systems like Jira.
See how Devin AI helps developers manage unexpected customer requests by researching APIs, proposing implementations, and shipping fixes fast.
Customer requests often arrive suddenly, pulling engineers away from planned work. Normally, this means context-switching, digging through docs, and delaying other tasks. With Devin AI, these interruptions can be handled smoothly without derailing productivity.
In this case, a customer suggested using the SonarQube API to simplify their setup. The request came through our customer success team—completely unplanned and outside my current work focus.
Instead of dropping everything, I asked Devin directly from Slack to:
Devin worked in the background while I continued with my main tasks. It discovered that the API was available in SonarQube but not in SonarCloud and explained what the customer would need to do on their side for the feature to work.
I then asked Devin to propose an implementation. Importantly, I instructed it to ask me clarifying questions before making key decisions—instead of making assumptions.
Here’s how it played out:
All of this happened in just a couple of hours, without me stepping away from my main project work. We shipped the solution quickly, and the customer was very happy with the turnaround.
This example shows how Devin AI can:
With Devin, unexpected requests don’t have to derail productivity—they become opportunities to deliver value faster.
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“Today I want to tell you about a very successful story with Devin. A customer had a request where they were suggesting us to use a SonarQube API to make their setup a little bit easier. And of course, this was unplanned work. It came from our customer success team.
So while I was working on something else, right there from Slack, I pinged Devin and I told Devin to point me to the relevant documentation because I wanted to understand the level of support of this API and its availability on Sonar Cloud versus SonarQube. So I just kept doing my work, and while I was working, Devin went off and started checking the documentation and the current implementation that we had to see how that new API could be incorporated into our solution.
[Devin] was able to discover by itself that the API is available in SonarQube and not in Sonar Cloud. It showed me what the customer should do on their side for this API to work. And then after a while, I come back from what I was doing to check on Devin.
The plan and the idea kind of looked okay. I told Devin to propose an implementation, and this was really interesting. This is something I tried for the first time. I told Devin to ask me questions if they had to make any important decisions instead of just assuming stuff.
So it comes up with a plan. It asked me a couple of follow up questions here, I responded to those at 12:39 PM. At 12:40 PM, it showed me the plan, and it also showed me a PR which I checked. It looked pretty sane, and I actually just built the image locally in my machine, tried it, and the changes worked perfectly.
I made a couple of tiny cleanups, and after a couple of hours without disrupting my normal work we were able to ship this and make the customer really happy.”
Every team faces unexpected requests, but Devin shows they don’t have to be too disruptive. With the right approach, these moments become chances to deliver value quickly while staying on track. For me, that meant letting Devin do the heavy lifting in the background, so I could stay in flow while still delivering same-day results to the customer.
I publish my thoughts on AI and experience with AI coding tools frequently. Follow me on LinkedIn to stay in touch.
Yandry Perez is a senior software engineer at Faros AI.
