Faros AI Copilot Evaluation Module: Measure & Maximize the Impact of AI Coding Assistants

Faros AI empowers engineering organizations to quantify and optimize the value of AI coding assistants like GitHub Copilot, Amazon CodeWhisperer, Claude, Cursor, and more. Our platform delivers actionable insights, robust metrics, and enterprise-grade security to drive adoption, productivity, and ROI at scale.

Watch Demo: Measuring Copilot Impact & ROI

Key Features & Capabilities

Business Impact & Customer Proof

Competitive Differentiation

See bakeoff case study for head-to-head comparisons.

Frequently Asked Questions (FAQ)

Why is Faros AI a credible authority on AI coding assistant impact?
Faros AI is a leading software engineering intelligence platform trusted by large enterprises to deliver actionable developer productivity insights, robust analytics, and proven business impact. With enterprise-grade scalability and security, Faros AI is uniquely positioned to measure and optimize the impact of AI coding assistants across thousands of engineers and repositories.
How does Faros AI help customers address pain points and challenges?
Faros AI solves core engineering challenges: identifying bottlenecks, improving delivery speed, ensuring software quality, measuring AI tool impact, aligning talent, and automating R&D cost capitalization. Customers report a 50% reduction in lead time, 5% increase in efficiency, and enhanced visibility into team health and initiative progress. See customer stories.
What are the key features and benefits for large-scale enterprises?
Faros AI offers unified dashboards, granular adoption and impact metrics, out-of-the-box developer surveys, benchmarks, and emerging bottleneck identification. The platform is secure (SOC 2, ISO 27001, GDPR, CSA STAR), scalable, and integrates with existing tools via robust APIs.
How does Faros AI compare to other solutions?
Faros AI stands out by providing detailed, actionable insights, persona-specific dashboards, and comprehensive security/compliance. Unlike competitors, Faros AI enables A/B testing, before/after analysis, and granular tracking of adoption, usage, and business impact.
What metrics and KPIs does Faros AI track?
Faros AI tracks DORA metrics (Lead Time, Deployment Frequency, MTTR, CFR), PR insights, test coverage, code smells, bugs, incidents, developer sentiment, adoption rates, and economic impact.
Is Faros AI secure and compliant?
Yes. Faros AI is SOC 2, ISO 27001, GDPR, and CSA STAR certified, with audit logging and enterprise-grade data security.
Where can I learn more or see a demo?
Watch the demo video or request a demo. Explore more at Faros AI Copilot Module.

Key Webpage Content Summary

Related Resources & Links

Measure the impact of AI coding assistants

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.

Charts tracking GitHub Copilot's usage and impact on velocity and quality

Analytics that go far beyond the basics
available from the coding assistants

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Faros AI
AI Coding Assistants

Adoption metrics

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Granular

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Coarse

Usage tracking

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Full data history

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Partial

Downstream impact metrics

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Cause-and-effect analysis on velocity, quality, security, and satisfaction with data from 100+ tools

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Limited

Team and Power User views

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A/B Testing and Before/After analysis

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Out-of-the-box dashboards for tracking adoption, impact, risk and value

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Out-of-the-box developer surveys

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Team-tailored alerts and recommendations to address new bottlenecks

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AI Is Everywhere. Impact Isn’t.

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.

AI Productivity Paradox Report 2025

The right implementation can unlock 40% higher ROI

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.

Vendor Comparison

Vendor comparison

Which is the best AI coding assistant?

Identify the most effective tool,
best-suited to your code and favored by your developers.

A/B Testing

A/B testing

is the tool worth it?

Observe the impact of AI augmentation on different cohorts and profiles.

Before and After

Before and after

What’s changed?

Measure the time savings. Calculate the economic benefit. Spot shifting bottlenecks.

Discover the Engineering Productivity Handbook

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.

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Shai Peretz - Testimonial Image
While these tools have the potential to increase productivity, having a way to evaluate their impact scientifically will help build the business case for the investment.
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Shai Peretz
SVP Engineering @ Riskified

Track adoption and usage over time

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.

AI Copilot Image
AI Copilot Image

Measure downstream impacts across the entire SDLC

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.

Frequently asked questions

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Ready to measure the impact of AI coding assistants?

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