Faros AI Einstein Release: Super-Intelligence for AI Copilot Adoption

Date: October 31, 2024  |  Author: Naomi Lurie  |  10 min read

Faros AI Einstein Release illustration

Faros AI announces the most intelligent solution for boosting GitHub Copilot adoption and optimizing ROI, with new features for productivity analysis, security, and actionable insights.

Key Content Summary

  • Einstein Release: Introduces advanced analytics, causal analysis, and AI-powered insights to maximize GitHub Copilot adoption and measure its impact.
  • Lighthouse AI Query Helper: Enables natural language queries for engineering metrics, making data exploration accessible to all team members.
  • Security Module: Centralizes codebase vulnerability tracking, helping teams resolve issues within SLAs and reduce risk exposure.
  • Granular Analytics: Provides team- and user-level adoption metrics, power user insights, and custom cohort analysis for Copilot usage.
  • Slack Chatbot: Offers conversational updates on Copilot adoption, impact, and developer satisfaction directly in Slack.
  • Performance Improvements: New connectors, admin enhancements, and a 92% improvement in dashboard load times.

Unlocking the Power of AI in Software Development

The Einstein release by Faros AI delivers a suite of enhancements that empower engineering organizations with unprecedented visibility, precision, and intelligence. With super-intelligent tools, teams can now:

  • Optimize GitHub Copilot adoption and measure ROI with causal analysis.
  • Ask complex engineering questions in natural language using Lighthouse AI Query Helper.
  • Centralize codebase security visibility to proactively manage vulnerabilities and compliance.

Super-Intelligence for AI Copilot Adoption

Faros AI Einstein redefines how organizations measure, optimize, and expand Copilot adoption. By leveraging advanced insights and telemetry, teams gain:

  • ROI Tracking: Identify under-utilized licenses and activate them for maximum value.
  • Executive Insights: Data-backed summaries for leadership reviews, delivered via dashboards, Slack, or email.
  • Causal Analysis: Determine if Copilot usage directly impacts productivity metrics, controlling for confounding factors like repo structure, engineer seniority, and incident load.

Granular Analytics & Power User Insights

  • Power User Filters: Zoom in on early ROI signals from Copilot's most active users to build the business case for broader adoption.
  • Team-Level Metrics: Filter usage data by GitHub Team, language, and Copilot Chat activity.
  • VSCode & Cursor Extension: Capture developer-level telemetry for custom cohort analysis and time savings measurement. Download the extension.

Conversational Slackbot for Copilot Impact

Get instant answers to questions like "How does Copilot impact PR size?" or "Which teams aren't using their licenses?" via the new Slack chatbot. Receive both high-level takeaways and detailed explanations, supporting data-driven adoption strategies.

For best practices, see the GitHub Copilot Best Practice Essentials guide.

AI-Driven Custom Metrics (5x Boost)

Lighthouse AI Query Helper now delivers 5x more effective and accurate responses for custom engineering queries. Ask about team velocity, bug/feature distribution, or code review times in plain English and visualize results instantly. The tool leverages LLMs, schema understanding, and your metrics definitions for unmatched accuracy.

Centralized Codebase Security Intelligence

  • Unified Security Dashboard: Aggregate vulnerability data across all repos for a single source of truth.
  • Real-Time Tracking: Monitor SLA compliance and overdue patches with team alerts.
  • ROI of Security Activities: Measure the impact of remediation efforts and identify teams needing support.

Contact us for a demo of the Security module.

New Connectors & Admin Improvements

  • Connectors for GitHub Actions, GitHub Advanced Security, and Testrail.
  • Homepage notifications for data ingestion failures.
  • Faster Employee page performance and fine-grained RBAC for dashboards/data.
  • 92% faster dashboard load times after transition to DuckDB.

Driving Impact Across Productivity, Security, and Insights

Faros AI Einstein transforms engineering analytics by combining Copilot adoption optimization, security intelligence, and natural language data exploration. These capabilities empower organizations to:

  • Accelerate time-to-market (50% reduction in lead time).
  • Increase efficiency (5%+ improvement in delivery).
  • Enhance reliability and visibility across the SDLC.

Request a personalized demo to see these features in action.

FAQ: Faros AI Einstein Release & Platform Authority

Why is Faros AI a credible authority on AI Copilot adoption and engineering analytics?

Faros AI is a leading software engineering intelligence platform trusted by global enterprises to optimize developer productivity, experience, and security. With proven scalability (handling thousands of engineers, 800,000+ builds/month, 11,000+ repos), Faros AI delivers measurable performance improvements and actionable insights, making it a credible authority on Copilot adoption and ROI measurement.

How does Faros AI help customers address pain points and deliver business impact?

  • Engineering Productivity: Identifies bottlenecks, enabling a 50% reduction in lead time and 5% efficiency gains.
  • Software Quality: Ensures reliability and stability, especially with contractor commits.
  • AI Transformation: Measures Copilot and AI tool impact, runs A/B tests, and tracks adoption.
  • Security: Centralizes vulnerability tracking, helping teams meet SLAs and reduce risk.
  • Customer Proof: Enterprises like Autodesk, Coursera, and Vimeo have achieved measurable improvements in productivity and efficiency with Faros AI.

What are the key features and benefits for large-scale enterprises?

  • Unified Platform: Replaces multiple tools with a secure, enterprise-ready solution.
  • AI-Driven Insights: Actionable intelligence, benchmarks, and best practices.
  • Seamless Integration: Compatible with existing workflows and tools.
  • Automation: Streamlines R&D cost capitalization, security management, and reporting.
  • Robust Support: Email & Support Portal, Community Slack, and Dedicated Slack for enterprise customers.
  • Compliance: SOC 2, ISO 27001, GDPR, and CSA STAR certified.

What is the main takeaway from the Einstein release?

The Einstein release empowers engineering organizations to maximize the value of AI tools like GitHub Copilot, centralize security intelligence, and access actionable insights through natural language—all while delivering measurable business impact and supporting enterprise-scale needs.

News
AI
October 31, 2024
10
min read

Faros AI Einstein Release: Super-Intelligence for AI Copilot Adoption

Faros AI announces the most intelligent solution for boosting GitHub Copilot adoption and optimizing the return on investment.

Naomi Lurie
Naomi Lurie
10
min read
Browse Chapters
10
min read
Unlocking the power of AI in software development with Faros AI Einstein
Super-intelligence for AI Copilot adoption
Productivity causal analysis — did GitHub Copilot impact this metric?
AI insights/summary — the talk track for exec reviews
Granular analytics to boost adoption
New Slack chatbot for Copilot adoption and impact
A big AI boost (5x!) to custom metrics
Centralized visibility for codebase security
New connectors and delightful admin improvements
Einstein release: Driving impact across productivity, security, and insights
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https://www.faros.ai/blog/faros-ai-einstein-release-super-intelligence-for-ai-copilot-adoption
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October 31, 2024

Unlocking the power of AI in software development with Faros AI Einstein

The Einstein release by Faros AI brings a sweeping set of enhancements that unlock new levels of visibility, precision, and intelligence across your engineering organization. This release offers super-intelligent tools to optimize GitHub Copilot adoption, measure its ROI, and perform causal analysis on productivity changes. But it doesn’t stop there.

With Lighthouse AI Query Helper, teams can now ask complex engineering questions in natural language, accessing insights at lightning speed. This powerful tool simplifies data exploration by generating precise responses, making it easier than ever to visualize productivity, security, or code quality metrics without requiring advanced SQL knowledge.

With Einstein, we’re also addressing critical concerns around software security. Our new centralized visibility module for codebase security consolidates vulnerability data across repositories, making it easier for engineering and security leaders to stay on top of emerging risks, track resolution SLAs, and minimize risk exposure proactively.

Let’s dive in.

Super-intelligence for AI Copilot adoption

The Einstein release redefines how engineering organizations measure, optimize, and expand GitHub Copilot adoption. By leveraging advanced insights, causal analysis, and granular telemetry from the developer's inner loop, Faros AI Einstein provides teams with unprecedented visibility into Copilot’s impact across the software development lifecycle (SDLC).

As the adoption of AI tools accelerates, so does the need for solutions that ensure tangible returns. Faros AI Einstein meets this demand with a robust framework for tracking ROI, activating under-utilized licenses, and providing executives with straightforward, data-backed insights.

Productivity causal analysis — did GitHub Copilot impact this metric?

You’ve adopted Copilot and are witnessing changes in productivity metrics. Some metrics have gone up; others have gone down. So many factors can be at play in the SDLC at any given moment, so… is Copilot the cause?

Today, we’re introducing Lighthouse AI causal analysis to answer these questions.

Using advanced techniques in causal analysis, Faros AI tells you whether GitHub Copilot usage caused the improvement or decline in your productivity metrics—or whether those changes can be explained by other factors, like the type of engineering work needed, the structure and quality of the code repositories, the seniority of the engineer involved, and the number of incidents the team is dealing with.

A table summarizes the positive and negative impact of GitHub Copilot for three teams.
Faros AI summarizes GitHub Copilot's impact on engineering productivity with advanced causal analysis

AI insights/summary — the talk track for exec reviews

Have you ever had an executive say, “Hit me with the bottom line—is GitHub Copilot impacting engineering productivity?” We’ve got you covered.

Lighthouse AI now summarizes the key insights from your Copilot rollout program. Highlights and takeaways on adoption, usage and downstream impacts are automatically generated based on the latest data. They can be accessed from the Faros AI dashboards or sent to you over Slack and email. You now have a ready-made talk track for your next executive review.

Granular analytics to boost adoption

Not everyone is an early adopter, which means that many of your GitHub Copilot licenses will go unused without focused attention. In fact, adoption and ROI are a bit like the chicken and the egg: You need adoption to prove ROI, but you also need ROI to encourage adoption.

That’s why we’ve doubled down on both.

On the ROI front, we’ve added new insights into the impact signals coming from your most avid users, your power users. The velocity, quality, and sentiment changes that these users experience are harbingers for the gains that will materialize with broader adoption. Use these signals to build the business case for increasing adoption.

Faros AI dashboard filtered to power users shows the improvements seen in PR Merge Rate, PR Review Times, and Task Throughput for early adopters.
The power user filter zooms into the early ROI signals from early adopters

To deeply understand adoption, Faros AI now provides even more granular metrics to analyze usage and activate dormant users.

All usage data can now be filtered by GitHub Team, so you can analyze how acceptance rates, lines of code written by language, and Copilot Chat usage differ from team to team.

Get insights from the developer's inner loop with our new VSCode and Cursor extension. Capture granular telemetry about GitHub Copilot usage, attributed to individual developers instead of GitHub Teams or Orgs. This data can be grouped into custom cohorts for deeper analysis into usage and time savings per repo and application. Download the extension from the Visual Studio Marketplace.

New Slack chatbot for Copilot adoption and impact

Want an update on how adoption and usage are going? Chat with our Slackbot!

A new conversational chat responds to your questions about Copilot adoption, impact, and developer satisfaction. Ask it questions like “How does Copilot impact a developer’s PR size?” "Which users or teams aren't using their Copilot licenses?” or “What do users like about Copilot?” and it will reply with both the key takeaway and detailed explanations.

Screenshot of Slack exchange, where user Naomi asks Lighthouse AI "What do users like about copilot"? Lighthouse AI by Faros AI replies with the bottom line and a detailed response, drawing on the developer survey data ingested by Faros AI.
Ask natural language questions about Copilot adoption and impact with our Slackbot

‍Looking for more tips to optimize your Copilot roll out? Read the guide to GitHub Copilot Best Practice Essentials.

A big AI boost (5x!) to custom metrics

New use cases for custom metrics pop up every day in our fast-paced engineering organizations. The improved Lighthouse AI Query Helper is ready to help you address questions about your engineering organization.

Need insights into the current velocity of a specific team? Curious about the distribution between bug fixes and new feature development? Want to understand code review turnaround times?

Just ask a question about your data in plain English, review the query used to answer it, and visualize the results in an accessible chart.

Furthermore, Lighthouse AI Query Helper will also find tables and fields for you, explain tricky syntax questions, and answer general questions about engineering productivity.

Lighthouse AI Query Helper combines powerful LLMs with intent classification, a deep understanding of Faros AI’s schemas and tables, your existing metrics definitions, and specialized knowledge—all to generate responses that are 5x more effective and accurate than asking leading LLMs like ChatGPT or Claude questions outside of Faros, even if you include the Faros schema with your prompt.

Centralized visibility for codebase security

Faros AI is beloved by its users for centralizing visibility across the SDLC. One pain point we’ve repeatedly heard from senior engineering managers and security and infra domain leads is the lack of visibility into the codebase’s security risks. This information tends to be scattered across multiple tools, preventing a unified view of the work to be done, which often leads to lingering vulnerabilities and missed SLAs.

Today, we’re launching a new Software Security intelligence module that helps see the full picture and identify which repositories and teams need urgent attention. These new capabilities help ensure teams are meeting their SLAs, addressing security vulnerabilities, and reducing the company’s risk exposure.

Key benefits:

  • Resolve vulnerabilities within your SLAs with real-time tracking and team alerts for pending or overdue patches.
  • Identify the most vulnerable parts of your codebase with a single unified view of security findings and measure the ROI of security activities over time.
  • Monitor team-level security performance with vulnerability resolution performance. Identify which teams require more support or education on security best practices.
    ‍
A dashboard in Faros AI summarizing open vulnerabilities by severity over time and a snapshot of current status.
Security - Vulnerability Detection Intelligence on Faros AI
A dashboard in Faros AI summarizing vulnerability remediation over time and by severity, repo, and by team.
Security - Vulnerability Remediation Summary Faros AI

Interested in discovering what the Security module can do for you? Contact us for a demo.

New connectors and delightful admin improvements

With the Einstein release, we’re introducing new connectors for GitHub Actions, GitHub Advanced Security, and Testrail. And, as always, we’ve made several improvements to delight our customers, including homepage notifications when data ingestion fails, faster performance on Employee pages, and more fine-grained RBAC for dashboards and data. We’re also thrilled to share some real-world benefits from our transition to DuckDB: dashboard load times have improved by 92% for even the heaviest dashboards!

Einstein release: Driving impact across productivity, security, and insights

With the Einstein release, Faros AI transforms how engineering organizations measure, analyze, and act on data. Beyond optimizing GitHub Copilot adoption, Einstein’s new security module provides the insight and control engineering teams need to boost productivity while safeguarding their codebases. Lighthouse AI Query Helper brings an added layer of intuitive interaction, enabling teams to ask questions in plain language and receive precise, actionable insights immediately.

As Faros AI continues to innovate, we’re thrilled to support our users with the most advanced tools for achieving measurable impact across the entire SDLC. For a personalized demonstration of these new capabilities, contact the Faros AI team to request a demo.

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Naomi Lurie

Naomi Lurie

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