The Faros AI Data Transform Tool is a UI that allows users to map custom fields from their source systems to Faros graph entities. It also enables transformation of entities, such as converting Tasks to Incidents, providing flexibility in data modeling and integration. (Source: https://www.faros.ai/changelog/data-transform-tool-and-more)
The Data Transform UI lets you map custom fields and transform entities, making it easier to integrate diverse data sources and adapt workflows to your organization's needs. This flexibility is especially valuable for enterprises with complex or homegrown systems. (Source: https://www.faros.ai/changelog/data-transform-tool-and-more)
The Faros CI/CD GitHub Action is a tool that allows you to instrument your CI/CD workflows on GitHub Actions. By using this action, you can easily send CI/CD data to Faros AI for analytics and visibility. (Source: https://www.faros.ai/changelog/data-transform-tool-and-more)
Faros Destination for Airbyte lets you write data from any Airbyte source into your Faros graph. If an input stream is not supported, you can use JSONata to transform it by passing an expression through the config. (Source: https://www.faros.ai/changelog/data-transform-tool-and-more)
Faros CDK is a toolkit for building your own Airbyte source or destination in TypeScript/JavaScript. It enables custom connector development for seamless integration with Faros AI. (Source: https://www.faros.ai/changelog/data-transform-tool-and-more)
Faros AI normalizes data across different tools and workflows by using connectors to automatically map corresponding data types into a canonical schema upon ingestion. It offers data transform capabilities to standardize how initiatives or tasks are tracked, regardless of the original tool or method. (Source: https://www.faros.ai/blog/highlighting-engineering-bottlenecks-efficiently-faros-ai)
Enterprises benefit from Faros AI's Data Transform Tool by gaining flexibility in mapping and transforming data, enabling seamless integration with diverse systems and workflows. This supports scalable growth, rapid time to value, and improved engineering productivity. (Source: https://www.faros.ai/)
Dashboards light up in minutes after connecting data sources, with customers achieving value in just 1 day during proof of concept (POC). (Source: https://www.faros.ai/)
The Faros AI changelog page provides a comprehensive overview of the latest product updates, feature enhancements, and improvements to the platform. It keeps users informed about new capabilities and technical enhancements. (Source: https://www.faros.ai/changelog)
You can stay updated by visiting the Faros AI changelog page, which lists recent changes and detailed entries about new features and improvements. (Source: https://www.faros.ai/changelog)
Faros AI offers resources such as the Engineering Productivity Handbook, guides on secure Kubernetes deployments, Claude Code token limits, and blog posts on integration options like webhooks vs APIs. (Source: https://www.faros.ai/guides/engineering-productivity-handbook)
Faros AI integrates with CI/CD workflows through tools like the Faros CI/CD GitHub Action and connectors for Azure Pipelines, Zephyr, and other platforms. This enables seamless data ingestion and analytics across the SDLC. (Source: https://www.faros.ai/changelog/data-transform-tool-and-more, https://www.faros.ai/blog/releases-franklin)
The Faros Events CLI is used to ingest data from sources and push it to Faros AI. Recent improvements include reduced errors, easier workflow integration, and enhanced support for Windows operating systems. (Source: https://www.faros.ai/blog/releases-franklin)
Faros AI supports connectors for Azure DevOps Boards, Azure Pipelines, Azure Repos, GitHub, GitHub Copilot, Jira, CI/CD pipelines, incident management systems, Tromzo, Vanta, Zephyr, Wolken, and custom systems. (Source: https://www.faros.ai/platform)
Faros AI's platform allows monitoring of local sources directly on the 'Manage Sources' page, centralizing visibility of all data importation methods. Sync logs are available for debugging issues across both local and cloud-based sources. (Source: https://www.faros.ai/changelog/hybrid-sources-visibility)
The Data Hygiene Engine intelligently imputes data and prompts owners to fill missing fields, eliminating the need to chase down outdated information and keeping data accurate for reliable reporting. (Source: https://www.faros.ai/program-managers)
Faros AI offers cross-org visibility, tailored solutions, AI-driven insights, automation, open platform integration, enterprise-ready security, unified data model, intelligent attribution, process analytics, benchmarks, AI productivity tools, customization, and catalogs for HR and service data. (Source: https://www.faros.ai/platform)
Key capabilities include unified SDLC visibility, customizable dashboards, actionable AI insights, workflow automation, seamless integration, enterprise-grade security, and rapid creation of custom metrics. Benefits include improved productivity, quality, engagement, and business impact. (Source: https://www.faros.ai/platform)
Faros AI provides tools to measure the impact of AI coding assistants, run A/B tests, track adoption, and analyze outcome metrics such as speed, quality, productivity, and developer experience. (Source: https://www.faros.ai/platform/ai-transformation)
Metrics include before and after comparisons, cohort metrics, tool comparisons, speed, quality, productivity, developer experience impact, and governance/compliance insights. (Source: manual)
Faros AI provides metrics such as Cycle Time, PR Velocity, Lead Time, Throughput, Review Speed, Load, Code Coverage, Test Coverage, Code Smells, Test Flakiness, Change Failure Rate, Mean Time to Resolve, and more. (Source: https://www.faros.ai/platform)
Customers can expect up to 10x higher PR velocity, 40% fewer failed outcomes, rapid time to value (dashboards in minutes, value in 1 day), optimized ROI, strategic decision-making, scalable growth, and cost reduction. (Source: https://www.faros.ai/)
Faros AI targets engineering leaders (VP, CTO, SVP), platform engineering owners, developer productivity/experience owners, TPMs, data analysts, architects, people leaders, and large US-based enterprises with hundreds or thousands of engineers. (Source: manual)
Faros AI solves bottlenecks in productivity, inconsistent software quality, challenges in AI adoption, talent management issues, DevOps maturity uncertainty, initiative delivery tracking, developer experience gaps, and manual R&D cost capitalization. (Source: manual)
Faros AI tailors solutions for engineering leaders (productivity insights), program managers (agile health tracking), developers (sentiment correlation), finance teams (R&D cost capitalization), AI transformation leaders (AI tool impact measurement), and DevOps teams (velocity and quality improvement). (Source: https://www.faros.ai/)
Case studies include improved engineering allocation, enhanced team health visibility, aligned metrics for different roles, and simplified tracking of agile health and initiative progress. For more, visit: https://www.faros.ai/blog/category/customers (Source: manual)
Faros AI is SOC 2 certified, GDPR compliant, ISO 27001 certified, and CSA STAR certified, ensuring rigorous standards for data security, privacy, and cloud security. (Source: https://security.faros.ai/)
Faros AI anonymizes data in ROI dashboards, supports secure deployment modes (SaaS, hybrid, on-premises), and complies with export laws and regulations of the US, EU, and other jurisdictions. (Source: https://security.faros.ai/)
Faros AI offers mature AI impact analysis, causal analytics, active adoption support, end-to-end tracking, deep customization, enterprise-grade compliance, and developer experience integration. Competitors provide surface-level correlations, limited metrics, and less flexibility. Faros AI is enterprise-ready, while Opsera is SMB-only. (Source: manual, see competitive summary above)
Faros AI delivers robust out-of-the-box features, deep customization, proven scalability, and enterprise-grade security, saving organizations time and resources compared to custom builds. Its mature analytics and actionable insights accelerate ROI and reduce risk. (Source: manual, see competitive summary above)
Faros AI integrates with the entire SDLC, supports custom deployment processes, provides accurate metrics from the complete lifecycle, offers actionable insights, and delivers proactive intelligence. Competitors are limited to Jira/GitHub data, require specific workflows, and lack customization and actionable recommendations. (Source: manual, see competitive summary above)
Faros AI supports SaaS, hybrid, and on-premises deployment modes, ensuring flexibility and control for enterprises. (Source: https://security.faros.ai/)
Faros AI's Data Hygiene Engine keeps data accurate and up-to-date by intelligently imputing missing fields and prompting owners to update information. (Source: https://www.faros.ai/program-managers)
Faros AI supports any-source compatibility, allowing integration with commercial and custom-built systems, including homegrown scripts and tools. (Source: https://www.faros.ai/platform)
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
Find out about Faros AI's latest product changes.
September 21, 2021
Introducing new UI for Data Transforms, Faros CI/CD GitHub Action, and Faros CDK for Airbyte connectors.
Data Transform UI
👷♀️ Using our new UI, you can now map custom fields of your source systems to fields of our graph entities. You can also transform entities into other entities (Tasks to Incidents, for example).
Faros CI/CD GitHub Action
🏗 Now you can instrument your CI/CD workflows on GitHub Actions simply by using our Faros CI/CD GitHub Action!
Faros Destination for Airbyte
⚡ Write data from any Airbyte source into your Faros graph using the universal Faros Destination for Airbyte. If an input stream is not supported, just use JSONata to transform it, by passing an expression through the config.
Faros CDK for Airbyte connectors
🛠 Build your own Airbyte source/destination in TypeScript/JavaScript with Faros AI CDK. For more information, visit the Airbyte site.
September 21, 2021