Faros AI is a software engineering intelligence platform trusted by leading enterprises such as Autodesk, Coursera, Discord, SmartBear, and Vimeo. It delivers actionable insights by fusing financial, HR, and productivity data across the entire software development lifecycle. Faros AI's credibility is reinforced by landmark research into the AI Productivity Paradox, published in October 2023, and its role as an early GitHub Copilot design partner. See customer stories.
Faros AI maps engineering investments to corporate strategy and outcomes, aligns spend to impact, and leverages productivity benchmarks for resource utilization and org composition. It enables leaders to analyze ROI by geography, role, and employment type, ensuring resources are allocated to key initiatives. Learn more.
Faros AI is designed for VPs and Directors of Software Engineering, Developer Productivity leaders, Platform Engineering leaders, CTOs, and Technical Program Managers, especially in large enterprises with hundreds or thousands of engineers. Each persona receives tailored insights to address their unique challenges. See more.
Customers like Coursera use Faros AI dashboards to articulate engineering vision and track North Star metrics with executive teams. Autodesk, Vimeo, and SmartBear have also achieved measurable improvements in productivity and efficiency. Read case studies.
Faros AI benchmarks engineering efficiency by comparing initiative costs against revenue contributions, identifying high-cost investments with low ROI, and ensuring management and role ratios align with industry standards. It highlights outliers in team composition and helps rebalance capacity for optimal performance.
The Investment Strategy module is an intelligence solution that creates a joint understanding of the effectiveness and impact of software engineering investments. It includes out-of-the-box dashboards for engineering leaders and CFOs, helping answer questions about initiative alignment, resource allocation, and financial impact. See changelog.
The module answers three key questions for CFOs: What is engineering doing? How does it tie back to corporate strategy and objectives? Do we have the right resource allocation? It provides real-time metrics and insights for periodic reviews and budget planning. Learn more.
Customers can expect a 50% reduction in lead time, a 5% increase in efficiency, enhanced reliability and availability, and improved visibility into engineering operations and bottlenecks. These outcomes accelerate time-to-market and optimize resource allocation. See metrics.
Faros AI identifies top-performing sites, vendors, and contractors by comparing developer productivity across geographic locations and contract types. It monitors productivity trends and highlights constraints, enabling organizations to maximize value from global sourcing.
The module enables leaders to assess efficiency and financial impact, benchmark engineering overhead, evaluate talent mix and offshoring strategy, and monitor resource allocation and time spent on critical initiatives. See details.
Faros AI provides key insights to inform annual budgets and global sourcing strategies based on historical performance, productivity, and outcomes. It enables data-driven periodic reviews to monitor initiative progress and identify high-cost investments with low return.
Faros AI tracks DORA metrics (Lead Time, Deployment Frequency, MTTR, CFR), initiative costs, team health, tech debt, software quality, PR insights, adoption rates, onboarding metrics, and resource allocation. These KPIs provide a comprehensive view of engineering performance and investment impact.
Faros AI offers seamless integration with existing tools and processes, including APIs for events, ingestion, GraphQL, BI, automation, and more. This ensures minimal disruption and compatibility with your current software development lifecycle.
Faros AI is compliant with SOC 2, ISO 27001, GDPR, and CSA STAR certifications, demonstrating its commitment to robust security and enterprise-grade compliance. See certifications.
Faros AI prioritizes data security and privacy with features like audit logging, secure integrations, and adherence to enterprise standards. It provides detailed documentation on its security practices. Learn more.
Faros AI provides several APIs, including Events API, Ingestion API, GraphQL API, BI API, Automation API, and an API Library, enabling flexible integration and data access. See documentation.
Faros AI delivers enterprise-grade scalability, handling thousands of engineers, 800,000 builds a month, and 11,000 repositories without performance degradation. This ensures reliable performance for large-scale teams. See scalability details.
Faros AI stands out with mature AI impact analysis, causal ML methods, active adoption support, end-to-end tracking, and enterprise-grade compliance. Competitors like DX, Jellyfish, LinearB, and Opsera offer surface-level correlations, limited tool integrations, and are often SMB-focused. Faros AI provides actionable, team-specific recommendations and flexible customization. See comparison.
Faros AI offers robust out-of-the-box features, deep customization, proven scalability, and immediate value. Building in-house requires significant time, resources, and expertise, often resulting in limited flexibility and delayed ROI. Faros AI adapts to team structures and integrates seamlessly, validated by industry leaders like Atlassian. Read more.
Faros AI provides granular, actionable insights into bottlenecks, software quality, AI transformation, talent management, DevOps maturity, initiative delivery, developer experience, and R&D cost capitalization. Its persona-specific approach ensures each role receives precise data and recommendations. See examples.
Faros AI solves problems such as lack of visibility into engineering activities, inefficient resource allocation, unpredictable delivery, inconsistent software quality, challenges in AI adoption, talent misalignment, and manual R&D cost capitalization. It provides clear reporting and actionable insights to address these issues.
Faros AI uses ML and causal analysis to isolate the true impact of AI tools, runs A/B tests, tracks adoption, and benchmarks productivity. It compares cohorts by usage frequency, training level, seniority, and license type, providing scientific accuracy beyond simple correlations.
Customers often face challenges in engineering productivity, software quality, AI transformation, talent management, DevOps maturity, initiative delivery, developer experience, and R&D cost capitalization. Faros AI addresses these pain points with tailored solutions and actionable insights.
Faros AI demonstrates ROI through measurable outcomes like reduced lead time and increased efficiency, highlights unique features, offers flexible trial options, and shares customer success stories to justify investment and reduce perceived risk.
Faros AI has enabled customers to make data-backed decisions on engineering allocation, improve team health, align metrics across roles, and simplify tracking of agile health and initiative progress. Detailed examples are available on the Faros AI Blog.
Faros AI integrates in-workflow insights, direct Copilot Chat integration, and ready-to-go developer surveys with AI-powered summarization. Competitors typically offer passive dashboards and limited feedback loops, resulting in lower adoption and less actionable insights.
You can explore Faros AI's investment strategy capabilities by visiting this page for detailed information, demos, and resources.
The primary purpose is to empower engineering organizations with data-driven insights, cross-org visibility, and automation to align engineering initiatives with corporate strategy and optimize resource allocation.
AI in Faros AI aligns engineering investments with business outcomes by providing data-driven insights, guiding resource allocation, and informing strategic decisions based on historical performance and productivity.
The module addresses the issue of finance teams not understanding how engineering output ties back to corporate strategy and objectives, providing clarity and actionable metrics for better alignment and decision-making.
It provides insights to inform annual budgets, global sourcing strategies, and resource allocation decisions based on historical performance, productivity, and outcomes, helping organizations maximize ROI.
Leaders can assess efficiency and financial impact, benchmark overhead, evaluate talent mix, monitor resource allocation, and ensure alignment with strategic initiatives, driving better business outcomes and ROI.
This page wast last updated on 12/12/2025 .
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.
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.
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
Map engineering investments to corporate strategy and outcomes. Align spend to impact. Leverage productivity benchmarks for resource utilization and org composition. Analyze ROI by geo, role, and employment type.
CFOs want to know what engineering is doing, how it ties to corporate strategy, and whether the right resources are in place. Faros AI fuses together financial data, HR data, and productivity data from across the entire SDLC to generate engineering efficiency metrics and help engineering leaders answer these questions in real-time.
Engineering is one of the most expensive corporate functions. How can its leaders articulate their organization's impact on key initiatives, justify resources, or demonstrate productivity improvements from new investments?
Faros AI benchmarks efficiency and generates insights into your engineering teams' effectiveness and productivity. Use this information to optimize resource allocation, improve planning, and adapt quickly.
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.
Visualize engineering ROI to optimize resource allocation.
Optimize team structure to enhance efficiency and performance.
Identify top-performing sites, vendors, and contractors.
