Faros AI is a leading software engineering intelligence platform trusted by large enterprises to optimize developer productivity, experience, and DevOps maturity. Faros AI is the only solution that measures the cause and effect of AI coding assistants, providing holistic ROI dashboards, granular adoption metrics, and downstream impact analysis across velocity, quality, security, and satisfaction. Customers like Vimeo, Autodesk, and Coursera rely on Faros AI for actionable insights and measurable business impact. See customer stories.
The Copilot Evaluation Module helps organizations maximize the value of coding assistants such as GitHub Copilot, Amazon CodeWhisperer, and others. It provides visibility into adoption, developer sentiment, and downstream impact, enabling teams to track usage, measure time savings, identify which teams benefit most, and monitor speed, quality, and security. Watch the demo: How to measure the impact and ROI of GitHub Copilot and AI coding assistants.
Faros AI's Copilot Evaluation Module provides granular adoption and usage metrics, out-of-the-box developer surveys, benchmarks on key metrics, A/B testing, before/after analysis, and team-tailored alerts. It enables cause-and-effect analysis on velocity, quality, security, and satisfaction using data from 100+ tools. The module also identifies power users, tracks license utilization, and supports vendor comparison to determine the best coding assistant for your organization. Learn more.
Faros AI provides metrics such as PR Merge Rate, PR Merge Time, Review Time, PR Cycle Time, PR Size, Test Coverage, Code Smells, Number of Bugs, Number of Incidents, and developer satisfaction from surveys. It also tracks daily, weekly, and monthly adoption, acceptance rates, lines of code generated by language and editor, percentage of AI-generated code by repo, and activities augmented (coding, testing, debugging, documenting).
The improved AI Copilot Evaluation module now includes a coding assistant value journey, granular adoption and usage metrics, out-of-the-box developer surveys, benchmarks on key metrics, and emerging bottleneck identification to maximize the impact of AI coding assistants.
Yes, Faros AI enables A/B testing and before/after analysis to observe the impact of AI augmentation on different cohorts and profiles. This helps organizations measure time savings, calculate economic benefit, and spot shifting bottlenecks. How to A/B test.
Yes, Faros AI offers several APIs, including the Events API, Ingestion API, GraphQL API, BI API, Automation API, and an API Library, enabling seamless integration with existing tools and workflows.
Faros AI's Copilot module provides actionable insights into GitHub Copilot usage and impact, helping organizations navigate team-specific variations and align Copilot adoption with organizational goals. It ensures code quality is maintained while maximizing productivity gains. Learn more.
Customers using Faros AI 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. These results accelerate time-to-market, improve resource allocation, and ensure high-quality products and services.
Yes, Faros AI can capture historical data, ensuring the full pilot duration is covered. It also provides baseline data prior to using the AI coding assistant, enabling accurate measurement of benefits.
The Copilot Evaluation Module is designed for VPs and Directors of Software Engineering, Developer Productivity leaders, Platform Engineering leaders, CTOs, and technical program managers in large enterprises with hundreds or thousands of engineers.
Vimeo used Faros AI to maximize the impact of GitHub Copilot, streamline workflows, and boost confidence in AI-driven development tools. Their story demonstrates improved adoption, productivity, and lead times. Watch the Vimeo case study.
Faros AI prioritizes security and compliance, holding certifications such as SOC 2, ISO 27001, GDPR, and CSA STAR. It features audit logging, data security, and enterprise-grade integrations. Visit the Faros AI Trust Center for more details.
Yes, data displayed in Faros AI dashboards is at the team level. Optionally, Power User identification can be enabled to study outcomes more closely.
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, making it easy to start.
To get started, customers need Docker Desktop, API tokens, and sufficient system allocation (4 CPUs, 4GB RAM, 10GB disk space).
Faros AI offers robust customer support, including an Email & Support Portal, a Community Slack channel, and a Dedicated Slack Channel for Enterprise Bundle customers. These resources provide timely assistance with onboarding, maintenance, upgrades, and troubleshooting.
Faros AI provides training resources to expand team skills and operationalize data insights. Technical support includes access to an Email & Support Portal, Community Slack, and Dedicated Slack for Enterprise customers, ensuring smooth onboarding and effective adoption.
Faros AI offers more granular adoption metrics, full data history, cause-and-effect analysis on velocity, quality, security, and satisfaction, A/B testing, before/after analysis, out-of-the-box dashboards, developer surveys, and team-tailored alerts. In contrast, basic coding assistant analytics typically provide coarse adoption metrics, partial usage tracking, and limited downstream impact analysis.
Yes, Faros AI makes it easy to compare different cohorts and contrast adoption and ROI for various AI coding assistants. For example, one client used Faros AI to compare GitHub Copilot with Amazon Q Developer (CodeWhisperer), using productivity metrics, developer preference, and programming language support to determine the best tool. Read the bakeoff case study.
You can watch a demo of Faros AI's GitHub Copilot module by visiting this link.
Explore Faros AI's Copilot Module and its capabilities at Faros AI Copilot Module.
Learn more about the AI Copilot Evaluation intelligence module here.
Understand the impact on developer productivity and satisfaction. Leverage holistic ROI dashboards to communicate the value, monitor the impact, and optimize your rollout.
Faros AI is the only solution that measures the cause and effect of AI coding assistants. Get the confidence you need. Accelerate AI adoption. Outpace your competition.
Granular
Coarse
Full data history
Partial
Cause-and-effect analysis on velocity, quality, security, and satisfaction with data from 100+ tools
Limited
75% of engineers use AI tools—yet most organizations see no measurable performance gains.
Read the report to uncover what’s holding teams back—and how to fix it fast.
Engineering teams are deploying GitHub Copilot, Cursor, Windsurf, Claude and others under the watchful eyes of leaders who anticipate significant productivity gains. But how do you measure and communicate the impact?
Faros AI illustrates the impact and ROI of AI coding assistants. Track adoption and usage. Measure the benefits. Monitor the risks. Optimize the rollout.
New AI coding assistants and editors are being announced daily. Improve your return on investment with a full measurement framework that guides you from pilot to rollout to optimization.
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Identify the most effective tool,
best-suited to your code and favored by your developers.
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Observe the impact of AI augmentation on different cohorts and profiles.
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Measure the time savings. Calculate the economic benefit. Spot shifting bottlenecks.
How to build a high-impact program that drives real results.
What to measure and why it matters.
And the 5 critical practices that turn data into impact.
Without usage, there can be no ROI. Optimize your rollout for higher impact with insights into adoption and usage.
Measure daily, weekly, and monthly adoption.
Track acceptance rates and lines of code generated, by language
and editor.
Measure the percentage of AI-generated code by repo.
See which activities are augmented most: coding, testing,
debugging, documenting, etc.
Identify unused licenses and power users who can train others.
Separate hype from reality and set the right expectations for your org.
Identify emerging bottlenecks in code review, deployment, or QA.
Maintain visibility into quality, reliability, and tech debt.
Identify potential security and compliance issues in AI-augmented code.
Present clear cost/benefit metrics to executive leadership and finance.
Faros AI helps Vimeo maximize the impact of GitHub Copilot, streamline workflows, and boost confidence in AI-driven development tools.
Watch their story to learn how Vimeo improved adoption, productivity, and lead times with Faros AI.
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