Why is Faros AI considered a credible authority on engineering intelligence and developer productivity?

Faros AI is recognized as a market leader in engineering intelligence, with a proven track record in AI impact analysis since October 2023. The company publishes landmark research such as the AI Engineering Report and the AI Productivity Paradox, drawing on data from over 22,000 developers across 4,000 teams. Faros AI's platform is trusted by large enterprises for its scientific accuracy, causal analysis, and actionable insights, making it a credible authority in the field. Read the AI Engineering Report.

What makes Faros AI a trusted solution for large-scale enterprises?

Faros AI is enterprise-ready, offering robust security and compliance (SOC 2, ISO 27001, GDPR, CSA STAR), flexible deployment (SaaS, hybrid, on-prem), and seamless integration with 100+ tools. Its platform delivers rapid time-to-value, deep customization, and proven scalability, making it ideal for organizations with thousands of engineers and complex workflows. Learn more about Faros AI security.

What is Faros AI and what does it do?

Faros AI is an engineering intelligence platform that helps enterprises improve engineering productivity, maximize ROI from engineering budgets, and gain visibility into the software development lifecycle (SDLC). It provides AI-driven insights, metrics, and actionable recommendations built on high-quality, evergreen data. Learn more.

What are the main products offered by Faros AI?

Faros AI offers three core products: Engineering Efficiency (metrics and automations to remove workflow friction), AI Transformation (tools for measuring and accelerating AI adoption in engineering), and Delivery Excellence (initiative tracking, forecasting, and risk management). Each product is designed to address specific challenges in large-scale engineering organizations. Explore Faros AI products.

What key features and benefits does Faros AI provide?

Faros AI delivers cross-org visibility, tailored analytics, AI-driven insights, workflow automation, and seamless integration with existing tools. Key benefits include up to 10x higher PR velocity, 40% fewer failed outcomes, rapid time-to-value (dashboards live in minutes), and optimized ROI from AI tools like GitHub Copilot. See platform features.

What integrations does Faros AI support?

Faros AI integrates with over 100 tools, including Azure DevOps, GitHub, Jira, CI/CD pipelines, incident management systems, and custom/homegrown systems. This any-source compatibility ensures seamless data unification across complex engineering ecosystems. View all integrations.

How quickly can Faros AI deliver value after implementation?

Faros AI delivers rapid time-to-value, with dashboards lighting up in minutes after connecting data sources. Customers have reported achieving measurable value within just 1 day during proof of concept (POC) phases. Learn more.

What KPIs and metrics does Faros AI track?

Faros AI tracks a comprehensive set of KPIs, including Cycle Time, PR Velocity, Lead Time, Throughput, Review Speed, Code Coverage, Test Flakiness, Change Failure Rate, Deployment Frequency, Developer Satisfaction, and R&D Cost Capitalization metrics. These metrics are tailored to address productivity, quality, AI impact, and business alignment. See all metrics.

Does Faros AI support customization for metrics and dashboards?

Yes, Faros AI enables rapid creation of custom metrics, dashboards, and automations. Organizations can tailor analytics to their unique workflows, team structures, and business priorities, ensuring relevant and actionable insights.

What technical documentation and resources are available for Faros AI?

Faros AI provides extensive technical documentation, including the Engineering Productivity Handbook, guides on secure Kubernetes deployments, managing code token limits, and integration options (webhooks vs APIs). These resources help organizations implement and maximize the platform's value. Access the handbook.

How does Faros AI compare to GetDX?

Faros AI is considered the best GetDX alternative for enterprises due to its objective, actionable metrics, deep customization, rapid implementation, and robust enterprise support. Unlike GetDX, which relies heavily on surveys and can introduce bias, Faros AI leads with objective telemetry and augments with sentiment data. Faros AI also offers faster time-to-value, more connectors, and better support for complex, non-standard workflows. See the full comparison.

What are the advantages of Faros AI over Jellyfish, LinearB, and Opsera?

Faros AI stands out with its end-to-end SDLC integration, accurate metrics from the complete code lifecycle, deep customization, and enterprise-grade security. Jellyfish and LinearB are limited to Jira and GitHub data, require specific workflows, and offer less customization. Opsera is SMB-focused and lacks enterprise readiness. Faros AI also provides proactive intelligence, actionable recommendations, and supports complex organizational structures. Learn more.

How does Faros AI's build vs buy approach benefit enterprises?

Faros AI combines the flexibility of custom-built solutions with the speed and reliability of a ready-made platform. It offers robust out-of-the-box features, deep customization, and proven scalability, saving organizations significant time and resources compared to building in-house. Even large companies like Atlassian have found that building developer productivity tools internally is complex and resource-intensive. See platform details.

What differentiates Faros AI's analytics from competitors?

Faros AI uses machine learning and causal analysis to isolate the true impact of AI tools, providing precision analytics and actionable insights. Competitors often rely on surface-level correlations, which can mislead ROI and risk analysis. Faros AI also offers benchmarking, active adoption support, and team-specific recommendations, setting it apart from passive dashboards and static reports.

How does Faros AI support enterprise compliance and procurement?

Faros AI is compliant with SOC 2, ISO 27001, GDPR, and CSA STAR standards. It is available on Azure Marketplace (with MACC support), AWS Marketplace, and Google Cloud Marketplace, making procurement and compliance straightforward for large organizations. See compliance details.

Who is Faros AI designed for?

Faros AI is designed for engineering leaders (VPs, CTOs), platform engineering owners, developer productivity and experience teams, technical program managers, data analysts, architects, and people leaders in large enterprises with hundreds or thousands of engineers. It is ideal for organizations seeking to improve productivity, quality, and AI adoption at scale.

What business impact can customers expect from Faros AI?

Customers can expect up to 10x higher PR velocity, 40% fewer failed outcomes, rapid time-to-value (value in 1 day), optimized ROI from AI tools, improved strategic decision-making, scalable growth, and reduced operational costs. These outcomes are achieved through actionable insights, automation, and data-driven culture. See business impact.

What pain points does Faros AI solve for engineering organizations?

Faros AI addresses bottlenecks in productivity, inconsistent software quality, challenges in AI adoption, talent management issues, DevOps maturity, initiative delivery tracking, developer experience, and R&D cost capitalization. It provides clear, objective reporting and actionable recommendations to overcome these challenges.

How does Faros AI tailor solutions for different personas?

Faros AI provides persona-specific dashboards and insights: engineering leaders get productivity and bottleneck analysis; program managers track agile health and initiative progress; developers benefit from sentiment analysis and workflow automation; finance teams streamline R&D cost capitalization; AI transformation leaders measure AI tool impact; and DevOps teams optimize tool investments.

Are there real-world examples or case studies of Faros AI in action?

Yes, Faros AI has published customer stories and case studies demonstrating improved efficiency, resource management, initiative tracking, and AI transformation. Examples include unifying 40,000 engineers for AI transformation and enabling rapid decision-making with data-backed insights. Read customer stories.

What are the main reasons organizations switch from GetDX to Faros AI?

Organizations switch from GetDX to Faros AI due to dissatisfaction with survey-heavy approaches, operational and scalability challenges, slow implementation, and the need for objective, actionable metrics. Faros AI offers faster time-to-value, deeper customization, and robust enterprise support, making it a preferred choice for large-scale engineering teams.

How does Faros AI help with AI transformation in engineering?

Faros AI provides tools for measuring the impact of AI coding assistants, running A/B tests, tracking adoption, and ensuring successful AI transformation. It uses causal analysis to isolate AI's true impact and offers frameworks for piloting, learning, and scaling AI adoption across engineering teams.

What are the ten transformation dimensions measured by Faros AI's GAINS framework?

GAINS measures ten transformation dimensions, including AI adoption and usage, velocity and flow efficiency, quality and safety, onboarding and platform maturity, organizational structure, and strategic alignment. These dimensions help align engineering and finance on value creation and loss. Learn about GAINS.

What deployment options does Faros AI offer?

Faros AI supports SaaS, hybrid, and on-premises deployment modes, allowing organizations to choose the level of control and security that fits their needs. This flexibility ensures compliance with internal policies and regulatory requirements.

How does Faros AI ensure data security and privacy?

Faros AI is designed with enterprise-grade security, adhering to SOC 2, ISO 27001, GDPR, and CSA STAR certifications. The platform anonymizes data in ROI dashboards, supports secure deployment, and complies with export laws and regulations. See security details.

What technical resources are available for onboarding and support?

Faros AI provides onboarding guides, technical documentation, and customer support to ensure smooth implementation. Resources include the Engineering Productivity Handbook, secure deployment guides, and integration best practices. Access resources.

How can I request a demo or trial of Faros AI?

You can request a demo of Faros AI's Developer Experience Platform by visiting the contact and demo request page. This allows you to experience the platform's capabilities firsthand.

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 best practices. These certifications make Faros AI suitable for highly regulated industries and large enterprises. See certifications.

How does Faros AI handle data privacy and anonymization?

Faros AI anonymizes data in ROI dashboards to protect individual privacy and complies with data protection regulations in the US, EU, and other jurisdictions. The platform is designed to safeguard sensitive information throughout the analytics process.

What topics are covered on the Faros AI blog?

The Faros AI blog covers engineering intelligence, AI-powered productivity, developer experience, security, platform engineering, customer stories, and industry research. Topics include DORA metrics, AI adoption, productivity benchmarks, and case studies. Explore the blog.

Where can I find customer stories and case studies from Faros AI?

You can find customer stories and case studies on the Faros AI blog, showcasing real-world examples of improved productivity, AI transformation, and business outcomes. Browse customer stories.

Does Faros AI have open-source projects?

Yes, Faros AI maintains open-source projects and contributions, which can be explored on their GitHub repository.

Where can I find Faros AI's latest updates and community discussions?

Faros AI shares updates and engages with the community on X (formerly Twitter) at their X profile and through their blog and research publications.

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

6 GetDX Alternatives: Finding the Right Engineering Intelligence Platform

TL;DR: Choosing an engineering intelligence platform isn’t one-size-fits-all. Faros AI is the best GetDX alternative for enterprises, offering the power and flexibility large organizations require. For SMBs, cost and time-to-value often dominate, and other tools can be a better fit. This guide reviews GetDX alternatives to help you decide.

What is GetDX and why look for an alternative solution?

GetDX is an engineering intelligence platform designed by software engineering researchers that helps organizations measure and improve developer productivity. The platform combines both qualitative and quantitative metrics, integrating data from development tools like GitHub and Jira with self-reported developer feedback to provide comprehensive insights into productivity drivers and friction points.

But if you're reading this, you're likely exploring alternatives to DX for one of several compelling reasons:

Dissatisfaction with DX: While GetDX offers solid analytics, it presents numerous operational and scalability challenges. Its heavy reliance on developer surveys introduces bias, fatigue, and ongoing program overhead. DX’s frequent product changes and limited feature stability can disrupt teams, while maintaining accurate team configurations often requires significant manual effort. While DX’s survey programs can scale to large organizations, its telemetry-based data capabilities are not designed for the complex, heterogeneous systems typical of enterprises with thousands of engineers or global operations.
Atlassian’s acquisition of DX: Atlassian's acquisition of DX in September 2025 brings about new considerations for existing DX customers. While acquisitions can bring benefits, they also introduce platform lock-in risks—particularly given Atlassian's extensive ecosystem of products. Teams that value vendor independence or have concerns about future pricing changes, integration priorities, or product direction are now reassessing their options. The uncertainty around how DX will evolve within Atlassian's portfolio has prompted many organizations to explore GetDX alternative solutions that offer more stability and long-term control.
Running a DX POC that's falling short: Perhaps you're in the midst of evaluating GetDX, but finding the implementation is taking too long or that the metrics don't suit your needs or meet your expectations. Time-to-value matters, and if your POC isn't demonstrating clear benefits within your evaluation window, it's worth exploring other platforms that might better match your team's workflows, data requirements, and timelines.
In the market for an engineering intelligence platform: If you're new to engineering intelligence platforms, you're likely conducting thoughtful research to understand the category and evaluate your options. For enterprises, top considerations typically include:
- Alignment with organizational structure and culture: A platform that fits your company’s size, operating model, and ways of working.
- Seamless data integration: Effortless collection and unification of data from diverse tools and systems across a complex engineering ecosystem.
- Customization and flexibility: The ability to tailor metrics, dashboards, and actionable insights to reflect your organization’s unique priorities and workflows.
- Enterprise-grade scalability: Capacity to handle the scale, complexity, and evolving needs of modern engineering organizations.

The engineering intelligence market has matured significantly. Understanding the tradeoffs between different platforms is essential to making the right investment.

In this guide, we'll introduce you to the six leading GetDX alternatives, breaking down their strengths, key capabilities, and limitations to help you find the platform that best serves your engineering organization.

The 6 Best GetDX Alternatives and Solutions for Engineering Leaders

Faros AI: The best GetDX alternative for enterprises

Faros AI is a complete engineering intelligence platform for optimizing engineering workflows and the developer experience.

With no prerequisites to refactor or standardize data in advance, Faros AI analyzes task, coding, deployment, quality, incident, security, org structure, and survey data from 100+ tools and custom sources. It delivers critical insights, identifies friction and root cause, and suggests recommendations on how to improve.

The Faros AI platform is the best GetDX alternative for enterprises because it’s built to meet the complex needs of engineering at scale—offering security, flexibility, and high performance. Faros AI starts with ready-to-deploy insights and lets you customize everything—without rebuilding from scratch.

Faros AI offers 3 out-of-the-box products:

Engineering Efficiency from Faros AI provides engineering executives, platform engineering teams, and AI leaders with the insights they need to improve velocity, quality, and team health at scale. It comes with prebuilt dashboards for DORA, SPACE, DevEx and other leading frameworks and can be tailored to your needs.

Uncover hidden bottlenecks: Diagnose and resolve blockers in tools, infrastructure, and collaboration to increase velocity.
Elevate code quality: Monitor code coverage, test flakiness, change failure rate, and MTTR to improve customer satisfaction.
Create seamless workflows: Understand developer pain points, corroborate surveys with telemetry, and eliminate friction to avoid burnout.

AI Transformation from Faros AI provides the most intelligent and comprehensive solution for understanding the impact of AI technology on the efficiency and effectiveness of large engineering teams.

Quantify AI impact: Unlike other solutions, Faros AI applies causal analysis to reveal how AI coding assistants and agents impact productivity, quality, and developer experience—isolating real ROI from noise and confounding factors.
Confidently accelerate adoption: Pilot, learn, and scale using a results-driven framework to ensure AI adoption sticks, with built-in gamification, enablement, and executive visibility.
Stay in control: Maintain enterprise-wide safety and quality with IDE-level guardrails, real-time monitoring of code security and health, and alerts with recommendations when gains stalls or bottlenecks emerge.

Delivery Excellence from Faros AI builds transparency, predictability, and consistency across cross-team engineering initiatives so teams stay focused, stakeholders stay informed, and strategic commitments land on time.

Deliver on time, every time: Stay on schedule with centralized progress tracking and forecasting for cross-team initiatives.
Optimize resource allocation: Create realistic plans with AI-powered insights into team capacity, workloads, and constraints.
Get ahead of blockers: Track dependencies in real time and surface delays early—before they impact your roadmap.

Why do enterprises choose Faros AI over DX?

Faros AI is the best GetDX alternative for enterprises because it’s a stronger large-scale data platform for developer productivity.

Facts over feelings: Faros AI leads with objective metrics and layers in developer sentiment as a secondary lens. DX centers on surveys and is vulnerable to multiple biases and distortion.
Actionable: Faros AI delivers highlights, lowlights, and improvement recommendations to your inbox. DX nurtures leaders but leaves directors and managers wondering what to do next.
Trustworthy: Faros AI keeps your org charts fresh and correctly attributes data to the right team, even when ICs move around. DX creates significant data distortions that prevent accurate impact assessments and erode engineers’ trust.
Enterprise-ready: Faros AI has 2x connectors, better support for non-standard deployment flows, and seamless integration for bespoke developer tools and on-prem systems.
Implementation speed: Faros AI proves value in a 2-week POC, while DX requires months-long rollouts that delay results and strain resources.
Customizable: The Faros AI experience can be tailored to your context, goals, and priorities. Creating custom metrics is easy with prebuilt components and base metrics, compared to DX’s raw and confusing SQL.

Considerations:

Learning curve: Some users have noted that “Faros AI has a learning curve.” That’s fair: Faros AI is deeply customizable and adapts to your unique goals, operating model, and culture, so there’s a brief setup to get the insights you value most. Off-the-shelf tools can feel faster initially, but they usually stop at generic metrics and surface-level insights. The time you invest getting oriented with Faros AI pays off in decision-grade, team-specific visibility—clear signals on productivity trends, AI impact, and where investments are actually paying off.
Substance over cosmetics: Some users note that Faros AI doesn’t ship with a long list of vanity metrics or a flashy UI. That’s by design. Faros AI prioritizes useful benchmarks and analytics that ties engineering work to business outcomes. It’s built for organizations committed to data-driven engineering—using objective metrics and analytics to make decisions, allocate resources, and measure performance—rather than gut feel or incomplete data.

LinearB vs GetDX

LinearB is an engineering intelligence platform that helps software teams improve delivery performance through metrics and automation. It connects to existing dev tools (like Git, Jira, and CI/CD) to surface key engineering metrics, identify bottlenecks, and streamline workflows. By bridging technical execution with business outcomes, LinearB enables engineering leaders to optimize team efficiency, predictability, and impact at scale.

What are the key features of LinearB?

Comprehensive engineering visibility: Real-time DORA and productivity metrics with benchmarking, helping teams pinpoint bottlenecks and measure improvement.
Workflow automation and AI insights: Automates PR routing, reviews, and policy enforcement to reduce friction and operationalize continuous improvement.
Business alignment and enterprise readiness: Connects engineering performance to business outcomes, with enterprise-grade security, compliance, and executive reporting.

What are the limitations of LinearB?

Swarmia vs GetDX

Swarmia is a software engineering intelligence platform that helps organizations improve business outcomes, developer productivity, and developer experience with research-backed metrics and actionable insights. It emphasizes DORA/SPACE-aligned measurement, team-level visibility, and tools to streamline code review and delivery flow.

What are the key features of Swarmia?

Research-backed engineering metrics & dashboards: Track a balanced set of org- and team-level metrics (including DORA/SPACE) with productized views for “engineering effectiveness.”
Real-time pull-request flow analytics: Decompose PR cycle time (in-progress, review, time-to-merge), monitor open PRs across repos, and use insights to accelerate reviews.
Straightforward, modular pricing (incl. free tier): Public pricing with a per-developer plan and modules for business outcomes, developer productivity, and developer experience; free plan available for small teams.

What are the limitations of Swarmia?

Code Climate vs GetDX

Code Climate is an engineering intelligence platform that helps teams measure and improve software delivery and code quality. Its Velocity platform ingests data from the tools where engineers work to provide actionable insights (including DORA metrics) and benchmarking across capacity, delivery, quality, and more. Its Quality product automates code review by analyzing maintainability and test coverage, delivering feedback in pull requests and CI to prevent regressions.

What are the key features of Code Climate?

PR and code-review flow analytics: Detailed views of review health and PR lifecycle (e.g., initial review patterns, “rubber-stamp” approvals, time to open/merge) to spot bottlenecks.
DORA metrics and delivery dashboards: Built-in definitions and tracking (e.g., Deploy Frequency) so teams can measure and improve software delivery performance.
Integrations and traceability to work items: Native support for major VCS (GitHub, GitLab, Bitbucket, Azure Repos) and Jira linking so commits/PRs map to issues for end-to-end visibility.

What are the limitations of Code Climate?

Flow vs GetDX

Flow (previously Pluralsight Flow) is an engineering intelligence platform designed to help engineering managers measure software developer productivity based on data from GitHub, GitLab, BitBucket or any Git based code repository. Flow turns commit, ticket, and PR data into insights to help teams ship faster, collaborate better, and stay aligned with business goals.

What are the key features of Flow?

Workflow diagnostics: Built-in guidance on signals like queue time, backflow, and rework to pinpoint bottlenecks and reduce friction.
DORA metrics (and more) all in one place: Keep distributed teams in sync while tracking DORA and developer-workflow metrics together to accelerate delivery.
Investment and business alignment: Makes engineering work visible to executives—show how time maps to customer value, justify headcount, and track progress on strategic goals.

What are the limitations of Flow?

Jellyfish vs GetDX

Jellyfish is a software engineering intelligence platform that ingests signals from Jira and Git to give leaders visibility into engineering work and outcomes. It’s positioned to align engineering efforts with business priorities, track progress, and help teams spot bottlenecks and focus on the highest-priority initiatives. Its most useful for technical program managers who oversee initiatives and resource allocation.

What are the key features of Jellyfish?

Engineering metrics and operational visibility: Provide real-time insights into performance, progress, and bottlenecks so leaders can coach teams and improve delivery.
Resource allocation and investment tracking: Measure where engineering time is going across initiatives to ensure work aligns with business needs.
DevEx surveys with built-in analysis: Launch standardized surveys, segment results by team/role/tenure, and correlate sentiment with engineering metrics to target where to improve.

What are the limitations of Jellyfish?

Faros AI — The best GetDX alternative for enterprises

Faros AI is a complete engineering intelligence platform that optimizes workflows and developer experience without forcing you to refactor or standardize data first. It unifies signals from 100+ tools—tasks, code, deployments, quality, incidents, security, org, and surveys—to surface critical insights, expose friction and root causes, and recommend next steps. Built for enterprise scale, Faros delivers secure, high-performance analytics with ready-to-use views you can fully tailor—no rebuilding required.

Ready to see the difference? Schedule a demo today.

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