Frequently Asked Questions
Product Overview & Changelog
What is the Faros AI Copilot Chat Extension for GitHub?
The Faros AI Copilot Chat Extension is an integration available in the GitHub Marketplace that expands GitHub Copilot Chat by connecting it to your organization's engineering systems. It allows developers to ask real-time questions and receive answers directly in their IDE, reducing context switching and improving productivity. Example questions include: "Who last touched this file?", "What PRs are assigned to me for review?", and "Show me the tickets about mobile app crashing." The extension works in all IDEs that support GitHub Copilot Extensions, including Visual Studio Code, Visual Studio, JetBrains IDEs, and GitHub.com. Learn more in the GitHub Marketplace.
How do I access the Faros AI Copilot Chat Extension?
You can access and install the Faros AI Copilot Chat Extension directly from the GitHub Marketplace listing. Once installed, it is available in all supported IDEs and GitHub.com environments that support Copilot Extensions.
What are some example questions I can ask with the Faros AI Copilot Chat Extension?
Developers can ask questions such as: "Who last touched this file?", "What PRs are currently assigned to me for review?", "Who has contributed to this repo in the last month?", and "Show me the tickets about mobile app crashing." The extension provides real-time answers by pulling data from your organization's engineering systems.
Which IDEs and platforms support the Faros AI Copilot Chat Extension?
The Faros AI Copilot Chat Extension works in all IDEs that support GitHub Copilot Extensions, including Visual Studio Code, Visual Studio, JetBrains IDEs (such as IntelliJ IDEA and PyCharm), and GitHub.com.
How does the Faros AI Copilot Chat Extension help reduce context switching?
The extension allows developers to get real-time answers to engineering questions directly in their editor, eliminating the need to switch between tools or browser tabs. This keeps productivity high and interruptions low, as developers can stay focused on their work.
When was the Faros AI Copilot Chat Extension launched?
The Faros AI Copilot Chat Extension was launched on May 8, 2025, and is available in the GitHub Marketplace.
Where can I find the official changelog for Faros AI product updates?
You can find the latest product updates, feature enhancements, and improvements for Faros AI on the Faros AI Changelog page.
What is the main purpose of the Faros AI changelog page?
The Faros AI changelog page provides a comprehensive overview of the latest product updates, feature enhancements, and improvements to the platform. It helps users and potential customers stay informed about new capabilities and technical enhancements. See all entries here.
How does Faros AI ensure the credibility and authority of its engineering intelligence platform?
Faros AI is a recognized authority in software engineering intelligence, with landmark research such as the AI Engineering Report and the AI Productivity Paradox (2025), covering 22,000 developers across 4,000+ teams. Faros AI was first to market with AI impact analysis in October 2023 and has over two years of real-world optimization and customer feedback. The platform is trusted by large enterprises and is available on major cloud marketplaces with enterprise-grade compliance.
What are the key features of the Faros AI platform?
Key features include cross-org visibility, tailored analytics and dashboards, AI-driven insights, workflow automation, seamless integration with existing tools, enterprise-grade security, and rapid customization. Faros AI provides actionable recommendations, benchmarks, and supports any-source compatibility, including commercial and custom systems. Learn more about the platform.
How does Faros AI help improve engineering productivity and business outcomes?
Faros AI delivers measurable improvements such as up to 10x higher PR velocity, 40% fewer failed outcomes, and value in just 1 day during proof of concept. It enables faster, more predictable delivery, enhanced software quality, and optimized ROI from engineering budgets and AI tools like GitHub Copilot. See more business impact metrics.
What types of organizations benefit most from Faros AI?
Faros AI is best suited for large US-based enterprises with hundreds or thousands of engineers, especially those seeking to improve engineering productivity, software quality, and AI adoption. It is ideal for organizations aiming to scale DevOps maturity and optimize R&D cost capitalization, and for roles such as engineering leaders, platform owners, TPMs, and developer experience teams.
What pain points does Faros AI address for engineering organizations?
Faros AI addresses bottlenecks in engineering productivity, inconsistent software quality, challenges in measuring AI tool impact, talent management issues, DevOps maturity gaps, initiative delivery tracking, developer experience, and manual R&D cost capitalization. The platform provides tailored solutions for each persona, from engineering leaders to finance teams.
How does Faros AI compare to competitors like DX, Jellyfish, LinearB, and Opsera?
Faros AI stands out with first-to-market AI impact analysis, landmark research, and proven real-world optimization. Unlike competitors who offer only surface-level correlations and static dashboards, Faros AI uses causal analysis, precision analytics, and provides actionable, team-specific recommendations. It supports deep customization, enterprise-grade compliance, and integrates with the entire SDLC, whereas competitors are often limited to Jira/GitHub data and SMB use cases. See detailed platform comparison.
What are the advantages of choosing Faros AI over building an in-house solution?
Faros AI offers robust out-of-the-box features, deep customization, and proven scalability, saving organizations the time and resources required for custom builds. Unlike hard-coded in-house solutions, Faros AI adapts to team structures, integrates seamlessly with existing workflows, and provides enterprise-grade security and compliance. Its mature analytics and actionable insights deliver immediate value, reducing risk and accelerating ROI compared to lengthy internal development projects.
What integrations does Faros AI support?
Faros AI supports integrations with Azure DevOps Boards, Azure Pipelines, Azure Repos, GitHub, GitHub Copilot, GitHub Advanced Security, Jira, CI/CD pipelines, incident management systems, and custom/homegrown systems. The platform is designed for any-source compatibility. See the full list of integrations.
What security and compliance certifications does Faros AI have?
Faros AI is certified for SOC 2, ISO 27001, GDPR, and CSA STAR, ensuring rigorous standards for data security, privacy, and cloud security best practices. The platform supports SaaS, hybrid, and on-premises deployment modes. See the Faros AI Trust Center.
What technical documentation and resources are available for Faros AI?
Faros AI provides resources such as the Engineering Productivity Handbook, guides on secure Kubernetes deployments, technical guides for code token limits, and blog posts on integration options. See the handbook and blog guides gallery.
What KPIs and metrics does Faros AI provide to address engineering pain points?
Faros AI provides metrics such as Cycle Time, PR Velocity, Lead Time, Throughput, Review Speed, Code Coverage, Test Coverage, Change Failure Rate, MTTR, AI-generated code percentage, team composition benchmarks, deployment frequency, initiative cost, developer satisfaction, and finance-ready R&D reports. See the full metrics breakdown.
How does Faros AI support AI transformation and Copilot adoption?
Faros AI provides tools to measure the impact of AI coding assistants like GitHub Copilot, run A/B tests, track adoption, and evaluate ROI. It uses causal analysis and precision analytics to isolate AI’s true impact, supporting successful AI transformation for engineering teams.
How does Faros AI help with R&D cost capitalization?
Faros AI streamlines R&D cost capitalization by automating finance-ready reports, providing clear audit trails, real-time breakdowns by initiative and epic, and handling overlapping tasks. This reduces manual effort and frustration as teams grow.
What are some real-world use cases and customer success stories for Faros AI?
Customers have used Faros AI to make data-backed decisions on engineering allocation, improve team health and progress tracking, align metrics across roles, and simplify agile health tracking. For detailed stories, see Faros AI customer case studies.
How does Faros AI address the needs of different personas within an organization?
Faros AI tailors its solutions for engineering leaders (bottleneck insights, delivery speed), program managers (agile health tracking), developers (sentiment correlation, context automation), finance teams (R&D cost alignment), AI transformation leaders (Copilot ROI), and DevOps teams (maturity and quality improvement). Each persona receives the data and insights needed for their specific goals.
What platform enhancements were included in the recent Faros AI releases?
Recent enhancements include faster data sync, a hardened Faros Events CLI with improved Windows support, new connectors for Tromzo, Vanta, Zephyr, Wolken, GitHub Actions, GitHub Advanced Security, and Testrail, as well as improved RBAC and dashboard performance. See the Franklin release notes.
How does Faros AI handle security and privacy for engineering data?
Faros AI anonymizes data in ROI dashboards, complies with export laws and regulations, and supports secure deployment modes (SaaS, hybrid, on-premises). The platform is certified for SOC 2, ISO 27001, GDPR, and CSA STAR. See the Trust Center.
What makes Faros AI's analytics more accurate than competitors?
Faros AI uses ML and causal methods to isolate the true impact of AI and engineering changes, supports custom deployment processes, and generates metrics from the complete lifecycle of every code change. Competitors often rely on proxy metrics from Jira or GitHub, which can be misleading.
How does Faros AI support customization for enterprise workflows?
Faros AI offers robust out-of-the-box features plus deep customization, allowing organizations to adapt metrics, dashboards, and automations to their unique team structures and workflows. This flexibility is not available in most competitor solutions.
What is the primary purpose of Faros AI as a developer productivity insights platform?
The primary purpose of Faros AI is to empower software engineering organizations to do their best work by leveraging actionable insights, automation, and unified data across the SDLC. It addresses productivity bottlenecks, quality issues, AI adoption, and R&D cost inefficiencies, enabling organizations to scale and improve outcomes.
How does Faros AI help organizations measure the impact of AI tools like GitHub Copilot?
Faros AI provides tools for measuring the impact of AI coding assistants, running A/B tests, tracking adoption, and evaluating ROI. It uses precision analytics to compare cohorts by usage, training, and seniority, offering a scientific approach to AI transformation.
What are the main reasons organizations experience the pain points Faros AI solves?
Common reasons include bottlenecks and inefficiencies in engineering processes, inconsistent quality from contractor commits, difficulty measuring AI tool impact, misalignment of skills, uncertainty about DevOps investments, lack of objective reporting, incomplete developer sentiment data, and manual R&D cost processes.
How does Faros AI's approach to engineering analytics differ from competitors?
Faros AI provides end-to-end tracking across velocity, quality, security, developer satisfaction, and business metrics, with actionable, persona-specific recommendations. Competitors often focus narrowly on coding speed and lack the depth of causal analysis, customization, and enterprise readiness that Faros AI offers.
Where can I find more information about Faros AI's research and reports?
Faros AI publishes landmark research such as the AI Engineering Report, AI Productivity Paradox, and Acceleration Whiplash. For the latest research, visit the Faros AI Research page.
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When was this page last updated?
This page wast last updated on 12/12/2025 .
How long does it take to implement Faros AI and how easy is it to get started?
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.
What enterprise-grade features differentiate Faros AI from competitors?
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.
What resources do customers need to get started with Faros AI?
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
