The Wolf Suite · Two tools · One decision

The question
everyone skips.

Wolflow asks whether your problem is genuinely ready for AI. Wolfpath maps exactly where to start. Both take under a minute.

Free · No account required · Under a minute

The obvious question

Why not just ask ChatGPT?

A raw LLM is optimised to help you succeed at whatever you ask. Put an AI idea to it and it will give you a thoughtful, encouraging answer — because you asked about your AI idea. That's not a flaw. It's what it's for.

These tools are built for a different goal entirely. Wolflow is optimised to tell you whether you should start. Wolfpath is optimised to show you how to start, always — with the cost of each step made visible so you can decide with your eyes open. Neither will encourage you for encouragement's sake.

The output is structured, consistent, and exportable. Not a conversation — a result you can show someone.

Most automation decisions fail at one of two points.

Before anything is built — wrong problem, wrong assumptions, wrong timing. Or when you start building — no clear entry point, no priority order, no sense of what's hard and what isn't. There's a tool for each moment.

◆ Wolflow

Should you start?

Seven sequential gates. Each one asks whether the conditions for AI to work actually exist. The moment a better answer exists — a rule, a process change, a simpler tool — Wolflow stops and tells you what it is. Most evaluations don't reach the final gate. That's the point.

Outputs: green / amber / red · exportable result · first move
Evaluate your problem →
◆ Wolfpath

Where do you start?

Paste any description of work — a job ad, a process doc, an email thread. Wolfpath decomposes it into discrete functions, sorts them by automation potential, and maps a path for each: a version you can ship this week, and a version you can build this quarter.

Outputs: prioritised path map · effort/impact scores · exportable
Map the path →

Three verdicts. All of them useful.

A red result isn't a failure. It's the tool doing its job — before you spend anything.

● Red — Don't automate

180-member martial arts studio wants ML churn prediction

Only 15 cancellations a year. The data volume doesn't support a model.

→ Simple rules-based flag + personal outreach caught 90% of at-risk members. No model needed.

● Amber — Hybrid path

HVAC company wants 7-day demand forecasting

Strong seasonal data, but the dispatcher has context the AI lacks.

→ Spreadsheet formula + weather API provides the forecast. Dispatcher reviews and adjusts.

● Green — AI is right

Security Operations Centre: 1,200 alerts a day

Analysts spend most of their time reading context before triaging.

→ Simpler filtering reduces volume but doesn't replace comprehension. AI is justified here.

Want to understand the framework in depth? The seven gates, the kill conditions, the philosophy behind exit-early evaluation — it's all documented.

How it works →

Know before you
commit to the wrong thing.

Both tools are free. No account required. Under a minute each.

Where are you right now?

Free · No account required · Takes about a minute