AI spend and ownership map
Every subscription, licence, API account and internal project, with its cost, owner and purpose.
AI advisory
AI Spend & Investment Review
In an AI Spend & Investment Review, I give you a clear view of what your business spends on AI, who owns each tool or project, and which spending is worth continuing. You get a findings report, practical cost controls and a prioritised list of what to continue, change or pause.
Discuss this service ↗Is this right for you?
Who this is for, and who it isn't.
A good fit if
- You pay for several AI tools, licences or APIs and nobody has the full picture
- AI bills are growing faster than you can explain
- Several teams are running AI experiments with unclear ownership or outcomes
- You need to justify AI budget to a board, investors or finance
Probably not the right fit if
- You use one AI tool with a predictable subscription: the cost is already visible
- You need a single AI project assessed in depth: a Project viability review is a better fit
- Your AI product works but costs too much per task: see AI quality and cost improvement
What you get
A practical result, not just a conversation.
Risk and duplication findings
Overlapping tools, unowned spend, unmanaged API keys and usage that is not linked to a business outcome.
Budgets, controls and alerts
Practical limits, reporting and alerting you can put in place with the providers you already use.
Continue, change or pause recommendations
A prioritised list, with the reasoning behind each decision, discussed in a working session with your team.
How it works
Three stages, agreed up front.
Scope and gather
I agree what is in scope with you and gather invoices, usage exports and a list of tools and projects from your team.
Map and analyse
I map spend to owners and outcomes, and identify waste, risk and gaps in control.
Review and decide
I walk through the findings with you. You and I agree which actions to take first.
Evidence
Relevant work you can check.
Published projects and guides that show this kind of work in practice.
Managing AI costs (free guide)
The cost-control approach used in these engagements, published in full: unit economics, cost ledgers, model choice and budget alerts.
Read the guide ↗FewzenAI WhatsApp agents case study
A platform for goal-oriented WhatsApp agents using OpenAI, with campaign management, CRM integration and interaction analytics. Teams could automate customer conversations while retaining control over agent behaviour and campaigns.
Read the case study ↗Common questions
Before you get in touch.
How much does an AI Spend & Investment Review cost?
Reviews are scoped after a short initial conversation and are usually fixed-price. The price depends on how many tools, projects or systems are in scope and how much information is already available, so you know the cost before work starts.
What do you need from us?
Access to invoices or billing exports, API usage dashboards where available, and time with the people who own or use each tool. The review does not require changes to any of your systems.
Can we do this ourselves instead?
Yes, and the free Managing AI costs guide explains the approach. The review is useful when you want an independent view, do not have time internally, or need findings that finance and leadership will trust.
What usually goes wrong with AI spending?
The most common problems are tools bought by individual teams with no central view, API keys with no budget limits, experiments that continue after they stop being useful, and costs that are not tied to any measurable outcome.
Work with me
Is this the right place to start?
Tell me what you are trying to achieve and you and I can work out the most useful next step. Start with a 30-minute call with me.