Frequently asked questions
Straight answers.
What clients ask before we start: how long it takes, what it costs, and how the work gets done.
Timelines
How long does an AI implementation take?
One use case typically goes from discovery to live use in about eight weeks: one to two weeks to pick the use case and define success, two weeks of design, three to four weeks of build and testing, then go-live with monitoring. A company-wide programme runs in waves of these eight-week cycles.
Why do most AI pilots never reach production?
Usually not because the model fails. Pilots stall because no one owns the result, success was never measured in money, the data is not connected, or there is no plan for security and failure. Each engagement fixes those four points before any code is written.
When will we see results?
The first measurable result is agreed at the start and usually appears within the first 90 days: time saved per task, cost per completed task, or pipeline and conversion changes for growth use cases.
Pricing
Where do the prices come from?
Prices are fixed by scope, not by the hour. Each one reflects the senior time involved, the deliverables and the risk carried. A fixed fee means you know the full cost before you start, and the incentive is to ship, not to bill more hours.
How much does AI implementation cost?
A Growth System Audit is $12,000. Building one AI use case and taking it live, fully done for you, is a $60,000 fixed fee. A Board AI Briefing starts at $15,000, and a reviewed AI roadmap is $2,500, credited toward the Audit.
What is included in the $60,000 build?
Discovery, design, the build itself, going live with security and monitoring, and support after launch followed by a full handover to your team. The running costs of the AI model are estimated up front so there are no surprises.
Is there a free way to start?
Yes. The AI Roadmap Builder produces a discovery-to-deployment roadmap for your use case in about a minute, and the Signal newsletter is free every Sunday.
Working together
Do you only advise, or do you build?
Both. Advisory sets direction; deployment means the system is built, tested and running in your business. Through Forward Labs, the work is delivered hands-on, not handed over as a slide deck.
Which cities do you work in?
New York, San Francisco, London, Dubai, Istanbul and Riyadh, with remote delivery elsewhere. The New York office is at 477 Madison Avenue.
What data do we need to start?
Less than most teams think. Data that exists but is scattered is the normal starting point. Discovery maps what is available and chooses a use case the current data can support.
How do we start?
Book a scoping call from the Products page or send a note through the Contact page with your use case and timeline.