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A tidy operations desk with blank sticky notes, a laptop and coffee

For operations

Turn AI into time back on routine work.

Give ops, finance and support teams prompts for the tasks they do every week, and track the hours saved on the use-case board.

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How does Team Tutor AI help operations teams?

Operations, finance and support teams get prompts for the documents, follow-ups and reports they repeat every week. Short lessons show where AI helps and where its output needs checking, especially with numbers. People log the time AI saved them on the use-case board, and it adds up on the manager dashboard.

Sound familiar?

Your teams repeat the same documents, follow-ups and reports every week. AI could help, but nobody has time to figure out how.

Start with the boring, repeated tasks. That is where an hour a week per person comes from.

Tarek RimanTarek Riman, Founder

How Team Tutor AI helps

Prompts for the tasks you already do

SOPs, vendor emails, meeting follow-ups, variance commentary. Fill in the blanks and copy.

Time saved, counted

People log what AI saved them on the use-case board. It adds up on the dashboard.

Practice on real work

Each path has a "try it" exercise with an example of a good answer.

Numbers you can trust

Lessons teach where AI helps and where it does not, especially with math.

Which training paths fit this team?

Start with these, then add or edit as you go.

All nine paths

AI for Finance and Ops

Use AI to write the words around your numbers, tidy up processes and save time on routine follow-ups, without trusting it with math it cannot do reliably.

8 lessons, 61 minutes

See the lessons
  1. ReadWhere AI helps, and where it doesn't7 min
  2. ReadWorking with numbers you can trust7 min
  3. ReadProcess documents, vendor emails and meeting follow-ups6 min
  4. Try itTry it: write month-end variance commentary10 min
  5. QuizCheck your understanding5 min
  6. ScenarioNumbers on the line: what would you do?8 min
  7. AI coachTry it: ask for the formula, not the answer8 min
  8. Role-playRole-play: show a CFO the real ROI10 min

AI for Customer Service

Answer customers faster and more consistently with AI drafts, while keeping the empathy, accuracy and privacy that customers expect from a real person.

9 lessons, 64 minutes

See the lessons
  1. ReadWhere AI fits in the support queue6 min
  2. ReadDrafting replies that sound human7 min
  3. ReadCustomer privacy and when a human must step in6 min
  4. Try itTry it: reply to a frustrated customer8 min
  5. QuizCheck your understanding5 min
  6. ScenarioIn the queue: what would you do?8 min
  7. CompareBefore and after: a late delivery reply6 min
  8. AI coachTry it: turn a solved ticket into a help article8 min
  9. Role-playRole-play: calm a customer charged twice10 min

Prompting That Works

A simple structure for writing requests that get useful answers the first time, with before and after examples from real work.

9 lessons, 67 minutes

See the lessons
  1. ReadThe five parts of a good prompt8 min
  2. ReadIterate: treat it like a conversation7 min
  3. Try itTry it: rewrite a weak prompt10 min
  4. QuizCheck your understanding5 min
  5. ReflectReflect: your first saved prompt5 min
  6. ScenarioWhen a prompt goes wrong: what would you do?7 min
  7. CompareBefore and after: a meeting recap prompt6 min
  8. AI coachTry it: build a reusable prompt template9 min
  9. Role-playRole-play: turn a vague request into a clear brief10 min

Questions teams ask

Which tasks do the operations prompts cover?

Everyday work such as writing SOPs, vendor emails, meeting follow-ups and variance commentary. Each prompt has blanks to fill in, a copy button and a risk level that says whether it is safe to use with client data.

How is time saved measured?

People share what they used AI for and the time it saved them on the use-case board. Those estimates add up on the manager dashboard, together with real examples you can show leadership.

Can AI be trusted with numbers?

Not blindly. The AI for Finance and Ops path teaches where AI helps with numbers and where it makes mistakes, and how to check its output before you use it.

Other teams

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