AI Stack Audit
Audit your AI stack before you buy another tool.
Find wasted AI spend, tool overlap, and what to fix next.
BINTU.ai generates a structured AI Stack Audit that maps your tools, seats, workflows, teams, and budget into a report you can actually use — whether you are advising clients or cleaning up your own stack.
Built around a staged workflow: planner → researcher → analyst → writer. That means the report is reasoned, not just summarized.
For consultants, operators, and teams trying to reduce AI tool sprawl without losing momentum.
What it helps you answer
The point is not just to list your tools. It is to understand what your current stack is actually doing.
Are we paying for tools or seats that don’t map to real workflows?
Microsoft Copilot is deployed across teams that do not appear to use it in repeatable, high-value workflows.
Which tools are overlapping, underused, or over-deployed?
Jasper and Copilot appear to overlap most heavily in marketing, where both tools support writing and ideation workflows.
Should we consolidate, expand, or hold the line?
The better move is to tighten deployment and measurement before adding more specialist tools.
Are some teams over-tooled while others are under-supported?
Marketing has the deepest AI coverage today, while HR appears lightly equipped relative to likely documentation and coordination needs.
What should we fix first if we want measurable value?
Start by right-sizing seats and defining workflow ownership before investing in additional automation.
What you get
A compact, decision-ready report.
The output is designed to help you understand where your current stack stands, what the real problem is, and what to do next.
How it works
Most AI reports jump straight from form inputs to final writing. This one doesn’t.
Planner
Frames the real question
Looks at your tools, teams, workflows, budget, and context to figure out what this audit actually needs to prove.
Researcher
Finds the right evidence
Pulls in relevant context, benchmarks, and sources so the report is grounded in more than just your form responses.
Analyst
Calculates what matters
Maps your stack into findings, variables, tables, and decision logic so the report can justify its conclusions.
Writer
Turns it into a usable artifact
Produces a clear report you can use with a client, stakeholder, or team without needing to translate it yourself.
Who it’s for
Built for people who need a sharper starting point.
Consultants
Use it as a sharp starting point for white-label AI advisory, client stack reviews, and faster discovery-light engagements.
Operators
Use it to understand whether your current AI spend is justified, where your deployment is weak, and what to clean up next.
Teams evaluating growth
Use it before adding another tool, expanding seats, or pushing AI more broadly across departments.
Start with a quick estimate
Get a directional estimate of potential AI waste.
Choose your industry and org size to get a rough starting point. Then run the full audit for the actual breakdown.
Industry
Org size
Work email
What the output feels like
Not generic commentary. A sharper point of view.
The goal is not to describe your tools back to you. The goal is to explain what the current stack is actually doing, where it is misaligned, and what the next move should be.
Example finding
Your stack is not necessarily too large.
The stronger issue is that deployment is broader than the workflows currently being measured, which makes spend harder to defend and value harder to prove.
This is the kind of sentence the report is designed to give you: specific, grounded, and useful in a real decision.
Example recommendation
Tighten deployment before adding more tools.
In this case, the better move is to right-size seat allocation, define workflow ownership, and set a small measurement baseline before introducing more specialist tooling.
The report is built to explain what to do next — not just what looks wrong.
FAQ
A few things people usually want to know.
Final step
Ready to see what your AI stack is actually doing?
Run the audit and get a clearer view of your current stack, the real problem behind it, and the next move that makes the most sense.