AI ROI advisory
Most enterprises measure AI adoption. Almost none measure AI return.
We identify where AI creates real economic value, implement it with cost and risk controls, and prove the return in the language of the CFO.
- Pilots multiply. Few reach production, and fewer still get measured once they do.
- Inference spend rises steadily. Almost nobody can explain which workflows are driving it.
- Legal and risk teams are asked to approve AI use cases they were never shown the economics for.
- The board asks for a return figure. What comes back is an adoption figure.
What we do
Six ways to make AI spend accountable
AI opportunity assessment
Rank forty ideas by economic value, not enthusiasm.
Workflow automation
Automate the workflow safely, not just quickly.
Model strategy and cost optimization
Explain what is driving the inference bill, then bring it down.
Governance, risk and compliance
Give legal an answer before they have to say no.
Executive advisory
Answer the board's questions before they are asked twice.
Enablement and training
Turn licenses your teams already have into measured output.
Our framework
The ROAI Method
A repeatable path from a long list of ideas to a governed, measured deployment.
Every engagement moves through the same four stages: measure what AI is actually costing and returning today, prioritize the workflows worth automating, implement with cost and risk controls built in, and govern the result so legal and risk do not shut it down six months in.
See the full methodWhat makes us different
We will tell you where AI should not be used
Every AI vendor and systems integrator is incentivized to find a reason to deploy. We are not. Part of every engagement is naming the workflows where the cost of getting AI wrong exceeds the value of getting it right, and saying so plainly, before you spend the budget finding out yourself.
Research
Executive-level research on AI return
Full papers on model economics, governance, and workflow automation. The executive summary is always free to read.
Daily AI briefing
What enterprise AI leaders need to know, every morning
A short, opinionated read on the AI news that actually affects budgets and governance. Free, and always public.
Accountability
The scorecard we hold ourselves to
We are a new firm without a portfolio of case studies yet. What we can show you is what we are willing to be judged against.
We are willing to say no.
The most useful thing an advisor can tell a client is where AI is the wrong tool for the job. Vendors rarely say this, because saying it does not sell more licenses.
We are not paid to spend your budget.
Systems integrators bill for scale. Model vendors bill for tokens. We are not compensated by how much you spend, which is what makes us credible when the answer is to spend less.
Numbers over adjectives.
Every recommendation we make states what it costs and who it does not suit. Percentages and dollar figures are claims. Words like streamlined and transformative are not.