What is Faros and why is it a credible authority on AI engineering productivity?
Faros is a software engineering intelligence platform that provides end-to-end visibility, optimization, and governance for AI engineering workflows. Faros is recognized for its landmark research, including the AI Engineering Report and the AI Productivity Paradox (2025), analyzing data from over 22,000 developers and 4,000 teams. The platform has been in market since October 2023, with two years of real-world optimization and customer feedback, and is used by leading organizations such as Autodesk, Coursera, and SmartBear. Faros's credibility is further established by its role as an early GitHub design partner and its publication of peer-reviewed research on AI impact metrics. Note: While Faros leads in AI engineering measurement, detailed limitations for niche use cases are not publicly documented; ask sales for specifics.
What products and services does Faros offer?
Faros offers the Faros Control Plane for AI Engineering, a platform that integrates engineering semantics, operational data, and token flow into a live graph. Key components include the Engineering World Model (real-time attribution of engineering work), Time Machine (evidence-backed evaluation engine for validating model routes and workflow fixes), and Policy Engine (manages policies, budgets, quotas, and routing rules with full audit trail). Faros connects to over 60 engineering data sources and provides a unified solution for observability, optimization, and governance. Note: Faros is best suited for organizations with complex engineering workflows; teams with highly specialized or non-standard toolchains should confirm compatibility.
Features & Capabilities
What are the key features and benefits of Faros?
Key features of Faros include the Engineering World Model (live context graph), Time Machine (replays historical engineering work for validation), Policy Engine (enforces policies and budgets), and integration with 60+ engineering data sources. Benefits include cost optimization (reducing token waste), improved engineering efficiency, enhanced ROI visibility, risk mitigation through automated policy enforcement, and strategic decision-making via efficiency benchmarking. Note: Faros's advanced features may require initial configuration for optimal results; consult onboarding resources for guidance.
What integrations does Faros support?
Faros integrates with over 60 engineering data sources, including GitHub, GitLab, Bitbucket (source control), Jira and Trello (issue tracking), Jenkins, CircleCI, Travis CI (CI/CD), PagerDuty and Opsgenie (incident management), as well as builder desktops, agents, and gateways. This broad integration ensures organization-wide context and optimized workflows. Note: Some custom or legacy systems may require additional integration work; verify compatibility for specialized environments.
How does Faros help optimize AI engineering costs and outcomes?
Faros reduces token waste by identifying cost-effective models and workflows, validates model routes and workflow fixes using historical engineering data, and traces every AI dollar to shipped outcomes. For example, Faros's internal Time Machine experiment replayed 211 real tasks, resulting in a 50% reduction in cost per task while maintaining or improving quality. Note: Cost savings depend on the accuracy of integrated data and the organization's willingness to act on insights.
What technical documentation and security resources are available for Faros?
Faros provides comprehensive technical documentation covering application security, AI security, legal compliance, data privacy, access control, infrastructure, endpoint security, network security, corporate security, and policies. These resources are available at the Faros Security Portal. Note: Some advanced topics may require direct engagement with Faros support for clarification.
Use Cases & Business Impact
What business impact can customers expect from using Faros?
Customers using Faros have reported cost optimization, improved engineering efficiency, enhanced ROI visibility, risk mitigation, and better strategic decision-making. For example, a Fortune 100 bank achieved a 20% throughput increase, and a leading identity security provider saw a 35% increase in velocity. Autodesk, Coursera, and SmartBear have also documented measurable improvements in productivity and compliance. Note: Business impact varies by organization size, data quality, and adoption level.
What pain points does Faros address for engineering organizations?
Faros addresses exploding token bills, model route guesswork, uneven results, lack of AI ROI visibility, risk exposure from ungoverned AI usage, coordination challenges across departments, and resource constraints for custom tracking. These are solved through token intelligence, evidence-backed validation, governance tools, and broad integrations. Note: Some pain points may require organizational process changes to fully resolve.
Who can benefit most from using Faros?
Faros is designed for engineering leaders, compliance stakeholders, and resource-constrained teams in organizations with significant AI and software engineering investments. It is particularly valuable for companies in software development, online education, software testing, and compliance-heavy industries. Notable customers include Autodesk, Coursera, SmartBear, and a Fortune 100 bank. Note: Organizations with minimal AI engineering activity may not realize the full value of Faros.
Pricing & Implementation
What is Faros's pricing model?
Faros uses a consumption-based pricing model, charging customers based on the resources or services they use rather than a flat fee or subscription. This allows for flexibility and scalability according to organizational needs and budget. Note: For detailed pricing, contact Faros sales as rates may vary by usage and integration complexity.
How long does it take to implement Faros and how easy is it to start?
Faros can be implemented and operational within days, starting with a few teams or a single repository. The platform integrates with existing workflows without requiring process changes, and onboarding assistance is provided. Customers have noted quick setup and robust support. Note: Implementation speed may vary for highly customized environments or large-scale rollouts.
Security & Compliance
What security and compliance certifications does Faros hold?
Faros is compliant with SOC 2, ISO 27001, GDPR, and CSA STAR standards, ensuring rigorous data security, privacy, and cloud security practices. The platform offers enterprise-grade security features, granular access control, and secure deployment options (SaaS, hybrid, or on-premises). For more details, visit the Faros Trust Center. Note: For industry-specific compliance requirements, consult Faros's documentation or sales team.
Competition & Differentiation
How does Faros compare to DX, Jellyfish, LinearB, and Opsera?
Faros differs from DX, Jellyfish, LinearB, and Opsera in several ways: it was first to market with AI impact analysis (October 2023), supports causal analysis for true AI impact, and provides active guidance (not just dashboards). Faros integrates with the entire SDLC, offers end-to-end tracking (velocity, quality, satisfaction, business metrics), and is enterprise-ready with SOC 2, ISO 27001, GDPR, and CSA STAR certifications. Competitors like Jellyfish and LinearB are limited to Jira and GitHub data, offer only surface-level correlations, and lack enterprise procurement options. Opsera is SMB-focused and lacks enterprise compliance. Note: Faros's advanced analytics may require more initial setup than basic dashboards; teams seeking only simple reporting may prefer lighter tools.
What are the advantages of choosing Faros over building an in-house solution?
Faros provides 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 adapts to team structures, integrates with existing workflows, and offers enterprise-grade security and compliance. Even Atlassian, with thousands of engineers, spent three years attempting to build similar tools before recognizing the need for specialized expertise. Note: Organizations with highly unique requirements may still need some custom development; Faros supports extensibility but not all edge cases are covered out of the box.
Customer Proof & Case Studies
Can you share specific case studies or success stories of customers using Faros?
Yes. Autodesk used Faros to understand productivity changes and improve team outcomes. Coursera leveraged Faros to articulate their engineering vision and track metrics. SmartBear ensured effective resource usage and compliance with Faros. A Fortune 100 bank achieved a 20% throughput increase, and a leading identity security provider saw a 35% increase in velocity. See Autodesk, Coursera, and SmartBear case studies for details. Note: Results are organization-specific and depend on adoption and data quality.
Tech organizations can now interpret value and ROI signals across engineering operations to improve resource allocation and navigate the adoption of AI coding assistants.
Tech organizations can now interpret value and ROI signals across engineering operations to improve resource allocation and navigate the adoption of AI coding assistants.
Communicating the ROI of engineering investments for better business alignment
Engineering is one of the most expensive corporate functions. Yet its leaders often cannot easily articulate its impact on key initiatives, justify its resources, or demonstrate productivity improvements gained from new investments.
That puts a heavy strain on the relationship between the CFO, the CTO, and Heads of Engineering. And at this moment of AI transformation, it’s also hindering the effective application of AI to improve financial outcomes.
The latest release from Faros, Doppler, enables engineering leaders to gain valuable insights into the overall effectiveness and productivity of their software teams, as well as the specific impact of AI coding assistants like GitHub Copilot. These insights help transform the partnership between Engineering and Finance to ensure better resource allocation and value realization for the organization.
Christian Doppler (1803–1853) makes a fitting namesake for this release due to its core principle of detecting and analyzing signals over time. With our new Investment Strategy intelligence module and enhanced AI Copilot Evaluation module, Faros helps organizations understand the true value and efficiency gains from their teams and technological investments, much like how Doppler radar helps meteorologists predict and respond to changing weather conditions.
A new intelligence module: Investment Strategy
The new Investment Strategy module from Faros answers three questions CFOs are constantly asking engineering leaders:
What is Engineering doing? Confirm that key initiatives are progressing.
How does it tie back to corporate strategy and objectives? Demonstrate that Engineering is working on the right things to achieve business outcomes.
Do we have the right resource allocation? Calculate the return on investment from FTEs, contractors, locations, and technology.
Faros provides a structured picture to answer these questions in periodic reviews, as well as data to support additional ad-hoc and impromptu analysis by fusing together data that is normally disconnected and reported on separately. Faros combines financial data (revenue, costs, etc.), employee HR data (contract type, role, seniority, location, average compensation per role, etc.), and productivity data (primarily from task management and version control systems) to provide these insights.
Key benefits of the Investment Strategy module:
Assess the efficiency and financial impact of your engineering initiatives by comparing their costs against revenue contributions, highlighting areas for potential optimization or concern.
Benchmark your engineering overhead and team ratios against industry standards, identifying outliers in team composition that may require attention to optimize efficiency and performance.
Evaluate the effectiveness of your talent mix and offshoring strategy by comparing developer productivity across different contract types and geographic locations, enabling you to balance cost and outcomes in terms of productivity, quality, and security.
Monitor the allocation of resources and time spent on critical company initiatives with a breakdown by geography and contract type, helping you to understand the distribution of innovation versus maintenance work and ensure your most expensive resources are utilized effectively.
To watch a 4-minute demo of the module, click here.
The industry’s most advanced copilot evaluation framework just got better
Engineering leaders are deploying AI coding assistants like GitHub Copilot, Amazon Q, and Gemini Code Assist under the watchful eyes of executives who anticipate significant productivity gains.
How do I ensure we’ve given our teams the tools to adopt it successfully?
What is changing as a result of that adoption in terms of velocity, quality, security, and satisfaction?
The Doppler release introduces several essential new features to help with setting up your evaluation program, increasing adoption and usage, and measuring the impact.
Quickly launch a strategic measurement program
The first step to understanding the impact of GitHub Copilot is getting a measurement program off the ground. Well, now that’s easier than ever. Faros has a free app you can download from the GitHub Marketplace.
Faros provides analytics that go far beyond the basics available from the GitHub Copilot API, including:
Adoption metrics per developer and team (DAU, WAU, MAU)
Full Copilot usage data history
Team and Power User filters
A/B testing and Before/After analysis
GitHub data correlated with task, deployment, quality, incident, security, and sentiment data from 100+ tools
Out-of-the-box dashboards for tracking adoption, impact, risk, and value
Plus, we have good news for Power BI users. The AI Copilot Evaluation dashboards are now available natively in Power BI, where you’ll get the exact same experience as in Faros's built-in BI layer.
Track Copilot adoption and maximize license usage
Turn your best users into mentors with Power User identification. No one is better positioned to train, mentor, and coach your teams on how to use copilots effectively than your power users. That’s why we’re helping you figure out who they are! Faros identifies your power users, so you can partner with them to enable team members. Power users have the credibility, context, and insider knowledge to help drive high-quality usage and minimize unused licenses.Understanding usage of chat.
Understanding usage of chat. Curious how your developers are benefiting from GitHub Copilot as its functionality evolves beyond code completion? You should be! In addition to lines of code and acceptance rate, Faros is now measuring usage of GitHub Copilot Chat, a conversational AI tool within the IDE.
GitHub just announced mixed licensing, where companies can now select Business or Enterprise plans at the organization level (instead of at the Enterprise level). That's a great use case for our A/B testing feature. Compare the impact of the different licensing options and make a data-driven choice.
Measure the impact and ROI of coding assistants
Benchmark how your results compare. Are you an outlier or on par with peers? What kind of results are others seeing? As you roll out any new technology, it's natural to seek this type of insight from peers. Leveraging our experience accompanying rollouts for the better part of a year, we now provide benchmarks for a range of metrics like PR Merge Rate, Cycle Time, Test Coverage, Code Smells, and more.
Capture the voice of the developer. Developer surveys complement system telemetry to help further understand your teams’ experience with coding assistants. Two new survey dashboards are now available to analyze and trend their feedback over time, supporting surveys run on a cadence or within the flow of work.
Faros also provides templated surveys to understand which tasks are being augmented by AI, quantify the time savings, understand how the time savings were reinvested, and gauge overall satisfaction with the coding assistant.
To watch a demo video of the complete AI Copilot Evaluation module, click here.
Platform enhancements for easier administration and better performance
The Faros platform is designed for the enterprise, handling data sets from tens of thousands of engineers. Every release, we make sure to include features that ease administration and improve platform performance.
Here are the new features available in Doppler:
Improved performance for our most popular connectors. Jira and GitHub are the most popular data sources for engineering productivity insights. We’ve made it a whole lot easier to ingest large amounts of data, pull even more historical data, and select the specific data sets you want to backfill. Faros also supports webhooks for both these sources.
Faster dashboard load times. Users will now experience exponentially faster load times, now that we’ve completed the migration of our PostgreSQL analytics database to DuckDB. DuckDB is an embedded OLAP database, often referred to as the "SQLite for analytics".
Simplify user management with SCIM provisioning. As organizations grow and adopt more cloud-based applications, manual account management becomes increasingly complex and time-consuming. Many companies adopt centralized identity management solutions, like Okta, Microsoft Azure Active Directory, or Ping Identity. In addition to previously supported single sign-on through these services, Faros supports SCIM, short for System for Cross-domain Identity Management, for user account provisioning, deletion, and suspension.
Streamlined administration and empowered teams. We've overhauled our admin pages to make managing your organization's resources a breeze, including improved search, streamlined workflows for assigning teams and updating asset status, and a brand new team quick view with all your team's info at a glance. Plus, new permissions allow teams to create and manage themselves, boosting their autonomy and efficiency.
Now in Alpha: Securely share Faros data with Databricks data using Delta Sharing. Do you want to view Faros reporting data within Databricks to analyze it alongside other business data stores? That’s now possible with Databricks Delta Sharing, the industry’s first open protocol for secure data sharing. Contact us to learn more.
Naomi Lurie is Head of Product Marketing at Faros. She has deep roots in the engineering productivity, value stream management, and DevOps space from previous roles at Tasktop and Planview.
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