Frequently Asked Questions

Product Information & Authority

What is Faros and what makes it a credible authority on AI engineering and developer productivity?

Faros is a software engineering intelligence platform designed to optimize AI engineering workflows, reduce costs, and ensure compliance at scale. Faros is recognized for launching the first AI impact analysis solution in October 2023 and publishes landmark research such as the AI Engineering Report, covering over 22,000 developers and 4,000+ teams. Its platform is built on years of real-world optimization, customer feedback, and scientific methods for measuring AI's true impact, making it a trusted authority for engineering organizations seeking actionable insights and measurable outcomes. Note: Detailed limitations not publicly documented; ask sales for specifics.

What products and features does Faros offer for engineering organizations?

Faros provides a unified control plane for AI engineering, including the Engineering World Model (a live context graph connecting tickets, agent sessions, commits, and CI verdicts), the Time Machine (an evidence-backed evaluation engine that replays historical engineering work), and a Policy Engine (for managing policies, budgets, quotas, and routing rules). Faros integrates with over 60 engineering data sources and offers observability, optimization, and governance in one platform. Note: Best fit for organizations seeking deep integration and outcome measurement; teams needing only basic cost dashboards may want to consider alternatives.

Features & Capabilities

What are the key features of Faros and how do they address engineering pain points?

Key features include token intelligence (tracking and optimizing token spend), model route optimization (finding the best price/performance for AI models), usage governance (enforcing policies and budgets), the Time Machine (validating changes before deployment), and integration with 60+ engineering data sources. These features help address exploding token bills, model route guesswork, uneven results, lack of AI ROI visibility, compliance risks, and coordination challenges. Note: Faros requires integration with engineering systems; organizations without such systems may see limited benefit.

Does Faros integrate with my existing engineering tools and workflows?

Yes, Faros connects to over 60 engineering data sources, including source control (GitHub, GitLab, Bitbucket), CI/CD pipelines (Jenkins, CircleCI, Travis CI), ticketing systems (Jira, Trello), incident management (PagerDuty, Opsgenie), and more. This ensures organization-wide context and optimized workflows without requiring workflow changes. Note: Some custom or proprietary tools may require additional integration work.

How does Faros help reduce costs and improve engineering outcomes?

Faros reduces token waste by identifying cost-effective models and workflows, cutting expenses from oversized models, retry loops, and unproductive work. The Time Machine feature validates model routes and workflow fixes using historical engineering data, increasing velocity and reducing code churn. Faros traces every AI dollar to shipped outcomes, providing actionable insights into ROI. Note: Cost savings depend on the quality of integrated data and organizational adoption.

Use Cases & Business Impact

Who can benefit 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 especially valuable for companies in compliance-heavy industries, software development, online education, and software testing. Notable customers include Autodesk, Coursera, and SmartBear. Note: Organizations without complex engineering workflows may not realize the full value of Faros.

What business impact and results have customers achieved with Faros?

Customers have reported cost optimization (e.g., Faros's internal case study showed a 50% reduction in cost per task across 211 real tasks), improved engineering velocity, enhanced ROI visibility, and risk mitigation. Autodesk used Faros to understand productivity changes, Coursera to track engineering metrics, and SmartBear to ensure resource usage and compliance. Note: Results may vary based on organizational context and implementation scope.

What pain points does Faros solve for engineering organizations?

Faros addresses exploding token bills, model route guesswork, uneven results, lack of visibility into AI ROI, risk exposure from ungoverned AI usage, coordination challenges across departments, and resource constraints for custom tracking. These are solved through token intelligence, the Time Machine, governance tools, and broad integrations. Note: Some pain points may persist if organizational processes are not aligned with Faros's approach.

Implementation & Onboarding

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, requires no process changes, and provides onboarding assistance. Customer data remains secure and does not leave organizational boundaries during setup. Note: Implementation time may increase for highly customized environments.

What feedback have customers given about Faros's ease of use?

Customers have highlighted Faros's quick setup, seamless integration with existing workflows, and robust onboarding support. Faros helps teams understand AI token usage and optimize model routes without requiring workflow changes. Customers also appreciate that their data remains secure during setup and usage. Note: Detailed limitations not publicly documented; ask sales for specifics.

Security, Compliance & Technical Documentation

What security and compliance certifications does Faros hold?

Faros is compliant with SOC 2, ISO 27001, GDPR, and CSA STAR. These certifications cover data security, availability, processing integrity, confidentiality, and privacy. Faros's Trust Center provides detailed information on its security practices and certifications. Note: For the latest certification status, visit the Faros Trust Center.

Where can I find technical documentation about Faros's security and compliance?

Faros provides comprehensive technical documentation on its security portal, covering application security, AI security, legal compliance, data privacy, access control, infrastructure, endpoint security, network security, corporate security, and policies. Note: Some documentation may require authorized access.

Pricing & Plans

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 organizations to scale usage according to their needs and budget. Note: For detailed pricing, contact Faros sales directly.

Competition & Differentiation

How does Faros compare to DX, Jellyfish, LinearB, and Opsera?

Faros launched AI impact analysis in October 2023 and publishes landmark research, giving it a maturity advantage. Unlike DX, Jellyfish, LinearB, and Opsera, which provide surface-level correlations, Faros uses ML and causal methods for accurate AI impact measurement. Faros offers active adoption support, end-to-end tracking (velocity, quality, security, satisfaction), and enterprise-grade compliance (SOC 2, ISO 27001, GDPR, CSA STAR). Competitors are limited to passive dashboards, narrow metrics, and SMB focus (e.g., Opsera). Note: Faros may require more initial setup for full customization compared to some SMB-focused tools.

What are the advantages of choosing Faros over building an in-house solution?

Faros offers 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 provides enterprise-grade security and compliance. Even Atlassian, with thousands of engineers, spent three years trying to build developer productivity tools before recognizing the need for specialized expertise. Note: Organizations with unique, proprietary requirements may still need some custom development.

Customer Proof & Case Studies

Who are some of Faros's customers and what industries do they represent?

Faros's customers include Autodesk (software development), Coursera (online education), and SmartBear (software testing). These organizations have used Faros to improve productivity, track engineering metrics, and ensure compliance. Note: For more case studies, visit the Faros website.

Can you share specific examples of customer success with Faros?

Yes. Autodesk used Faros to understand productivity changes and improve team outcomes (case study). Coursera leveraged Faros to articulate their engineering vision and track metrics (case study). SmartBear used Faros to ensure effective resource usage and compliance (case study). Note: Outcomes depend on organizational context and adoption.

RUN YOUR SOFTWARE FACTORY EFFICIENTLY

Stop token maxxing.
Start outcome maxxing.

Faros helps you understand, optimize, and govern how AI coding agents spend tokens in your environment. Reduce your cost per outcome shipped, while continuously improving your AI coding efficiency. 

MAXIMIZE YOUR AI CODING ROI

Stop token maxxing.
Start outcome maxxing.

Faros connects your AI coding spend to the outcomes it ships, routes each task based on evals built from your own code, and keeps usage in policy as you scale.

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THE WILD WORLD OF AI CODING AGENTS

Skyrocketing AI spend, uneven outcomes

Every builder now runs a fleet of coding agents. Every team is improvising on best practices, picking models on instinct and paying frontier prices for work that a cheaper route ships just as well. Every organization is building a software factory, but nobody is operating it like one.

Exploding token bills

Exploding token bills

Armies of agents default to the latest, costliest models.

Model route guesswork

Model route guesswork

Model prices vary by 10x, but nobody knows which is best.

Uneven results

Same tools, different results

AI budgets get devoured without uniform outcomes across teams.

WHAT IS FAROS

The complete token engineering platform

Faros orchestrates the tokens flow through your AI coding agents to minimize waste, maximize quality of output, and ensure compliance with organizational guardrails. It connects to your coding agents, harnesses, and engineering systems, and joins every session, commit, and PR into one live, reconciled model of your token flow. It mines your code history for the model routes and context that offer the best price/performance specific to your tasks. And then it enforces your approved model routes, budget controls, and compliance policies through a model router (your or ours).

Faros platform flow: spend, AI work, commit, PR, outcomeFaros platform flow: spend, AI work, commit, PR, outcome

Cut token waste

Stop spending on oversized models, retry loops, and work that never ships.

Increase velocity

Complete more coding tasks, with precision context and fewer prompts.

Reduce code churn

Ship agent code that provides human-grade quality and holds up in review.

Minimize risk

Keep teams on approved models and budgets, and capture full audit trails.

OUR SECRET SAUCE

Data, decisions, and outcomes you can trust

Faros is a closed-loop system for AI coding work that measures what your AI engineering produces and feeds it back into the next routing decision. Unlike general purpose solutions, Faros gives you a complete picture of your AI work and its outcomes, and uses patent-pending evaluation methods to implement optimizations contextual to your environment, giving gives you observability, optimization, and governance, across all your AI coding efforts, in a single, scalable, trustworthy platform, with data you can rely on, and decisions that maximize outcomes in your environment.

Engineering world model: attribution, analytics, actions, eng, ops, tokens

AI engineering world model

An exhaustive graph, built on your own live data, that tracks your AI coding work with precision, so you can attribute token usage to verified outcomes with high trust.

Time machine: merged PR replayed and scored

Time machine

A proprietary evaluation engine that leverages your own code history to pinpoint model routes that produce the best code at the lowest cost, validated on your organization's real work.

TRUSTED BY THE WORLD'S TOP TEAMS

Advancing those who build

"With Faros, when something changes in our productivity, we can understand why it happened and take action to help teams be more successful."

Ben Cochran
VP of Developer Enablement
,
Autodesk
Smiling man with a beard and medium-length hair, featured on the Faros AI website.
Smiling man with a beard and medium-length hair, featured on the Faros AI website.

“Faros has become essential in communicating our value clearly and securing buy-in at the executive level. Today, I articulate our engineering vision and track north star metrics seamlessly.”

Mustafa Furniturewala
SVP of Engineering
,
Coursera
Smiling young man in a polo shirt, representing the approachable team culture at Faros AI on their website.
Smiling young man in a polo shirt, representing the approachable team culture at Faros AI on their website.

"The data in Faros is so good that whether my CEO looks at it or a team member looks at it, it's not an issue. I use the insights to make sure we're using our resources effectively."

Vineeta Puranik
Chief Technology Officer
,
SmartBear
Portrait of a woman with shoulder-length hair wearing a floral blouse, representing the team on the Faros AI website.
Portrait of a woman with shoulder-length hair wearing a floral blouse, representing the team on the Faros AI website.

Stop token maxxing.
Start outcome maxxing.

Run it live in your own org. Work with us to measure what your AI coding ships, and determine which models work best on your codebase.

LATEST UPDATES

What’s new at Faros

AI Industry

What is a software factory? How it works

Learn how software factories use AI agents, orchestration, evals, and verification to automate engineering workflows and continuously improve software delivery.

AI Industry

How to track AI coding costs across teams

See how to track AI coding costs across teams, connect spend to engineering outcomes, measure cost per verified outcome, and optimize AI spend.

AI Industry

Why cheaper AI models can cost more: The hidden model tax explained

Uncover the hidden “model tax” in cheap AI coding models. Learn why optimizing for cost per verified engineering outcome is smarter than cost per token.