Evidence tier Source Confirmed · 4 captures on record
What the publisher says
As described on AWS Marketplace.
Faros gives engineering leaders the visibility and control to maximize AI engineering outcomes, while managing costs and keeping every team within policy.
As AI coding agents get embedded deeper in everyday engineering work, leaders face rising token bills and uneven outcomes across their teams. Faros ties that spend to the outcomes it produced and shows where efficiency leaks, down to the root cause. From there it points work at the models and patterns that perform, and enforces the policies that govern how tokens get spent.
Show the rest of the publisher’s description (6 more lines)
At the center is an engineering context graph that mirrors how your organization actually builds software, linking work, activity, and outcomes into one coherent view. Every number ties back to a real system of record, instead of three vendor dashboards telling three different stories.
Core capabilities
Observability - Trace every token and model call back to the team, task, and code it produced. Productive work and waste separate out team by team, instead of hiding in one opaque total.
Diagnostics - Find where efficiency leaks, what is causing it, and the evidence behind it. Ask the agent follow-up questions when you want to dig deeper.
Optimization - Match the right model to each job, and turn what already works into reusable skills and context, so strong results are not limited to a few senior engineers.
Governance - Keep AI adoption compliant as it scales. See what is being used, by whom, and whether it is within policy, without slowing delivery down.
Highlights
Highlighted by the publisher on AWS Marketplace.
Faros shows what your AI spend actually shipped. Every token and model call ties back to the task it ran and the code it produced, so you can see which teams turn spend into output and which just burn it.
Faros finds where your engineering efficiency leaks and why. It surfaces the root cause and the evidence behind it, from slow reviews to models misapplied to routine work, and lets your team interrogate the finding instead of guessing at it.
Faros matches each task to the model that has actually shipped working code on your repos. It does so by learning from your code history, then turns what works into shared skills and context, so strong results are not limited to a few senior engineers.
Agent build and provenance
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Plans and pricing as listed
1 listed- Units
Refund terms
As stated by the publisher on AWS Marketplace.
For monthly users, the first month is a free trial. For annual users, please contact us for a free POC first. After that point, all fees are non-cancellable and non-refundable except as required by law.
Sources
Linked repositories
Unknown means this listing does not publish a repository. It is not a statement that the code is closed, and a linked repository is not a claim that the publisher wrote it: the registry computes that relationship privately and does not publish it.
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