AI Use-Case Audit

You've been asked to implement AI at your company.
Where do you start?

The hardest part of AI isn't building. It is choosing the right use-case and designing the plan. Describe a workflow and we'll tell you if it's worth it, i.e. are agents even required, costs, and the right architecture.

Score my workflow →
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AI Use-Case Audit
100% BIU 🔗 Editing

Describe in plain English your workflow that you'd like us to evaluate.

Attach a list if you have multiple workflows.

List your tasks or attach a file.

Got it — your ranking is on the way.

We review every submission personally and send back a stack-ranked shortlist with the why.

How it works

From a blank page to a clear first move.

I

Describe the workflow

Tell us, in plain English, what the process is and where do you think AI should be implemented.

II

We score each one

Fit, effort to build & maintain, the best model, and cost to run and most importantly: is it a good bet, a simple automation, or one to skip, as well as much more.

III

Start with confidence

A stack-ranked shortlist with the why. You can ask questions to go deeper whenever you need.

What we score, for every use case
◆ Fit

Fit

Does it fit how your company actually operates and does it even require AI agents?

◆ Effort

Effort

What it takes to build it — and keep it running.

◆ Model

Model

The right architecture and model for the job.

◆ Cost

Cost

What it actually costs to run, per month.

The verdict

Good bet, simple automation, or skip.

✓ Build it⚙ Automate it✕ Skip it
Why this matters

Most AI projects are chosen wrong.

Teams build agents for things that never needed one.

A script, a rule, or a better form would have done the job for a fraction of the cost.

Wasted spend is the default outcome.

Money and weeks of engineering go into agents that underperform, stall, or get quietly shut off.

Nobody runs an objective fit check first.

Most teams commit to building before anyone asks the hard question: will this actually work?

Guessing is expensive. Finding out is cheap.

Five minutes here can save you a quarter of build time.

The pattern we see

Most AI pilots are picked by hype, stall six months in, and burn the budget.

It doesn't have to start that way.
Five minutes describing a workflow tells you whether it's worth a single day of build before you commit a quarter to it.

Who builds it

Operators who know which AI bets pay off.

We're seasoned operators who have built and exited infrastructure start-ups, and were super early at Snowflake. We built the infrastructure for data cloud at scale and trained foundational models, so we know a good opportunity from an expensive distraction.

Early at SnowflakeTrained foundational modelsBuilt & exited infrastructure startups

Stop guessing where to start.

Describe a workflow or drop in your list. We'll send the ranked shortlist.