AI USE CASES FOR BUSINESSES

WHERE TEADMISI’S AI IS ALREADY SAVING HOURS AND MONEY

Do the math on what you’re losing: how many minutes of your team’s time evaporate every day searching, rewriting or repeating the same things?
At Teadmisi we don’t sell “AI”. We sell time recovered and decisions that no longer depend on “the person who knows”.

Below you’ll find some AI use cases from companies we work with. In some projects we combine AI with automation tools such as n8n, to connect documentation, processes and internal applications.
You’ll see 9 real ways to do this, grouped by the type of organisation that is already seeing the impact on its bottom line.

CONSULTING FIRMS AND PROFESSIONAL PRACTICES

Use case 1 – Intelligent search over case files and regulations

Real problem: each consultant loses 3.2 hours per week digging through 12,000 files.
When the senior is on holiday, answers are delayed by 48 hours and the client logs it as “late delivery”.

Approach: an internal RAG system that answers in natural language using only your documentation (zero hallucinations). If you want a detailed explanation of what an internal RAG system is, you can read this article.

  • Measured results:
  • 80% less time spent searching
  • 192 hours per month recovered
  • 4× ROI in 10 weeks

Use case 2 – Internal support for consultants

Real problem: the same partner gets interrupted 47 times a day with questions like “which template should I use?” or “how do I invoice extra-EU work?”.
Onboarding new hires takes 6 weeks before they become productive.

Approach: an assistant connected to manuals, FAQs and quality procedures that answers in under 3 seconds.

  • Measured results:
  • 70% fewer internal tickets
  • Onboarding reduced to 3 weeks
  • Partner recovers 1.5 hours per day for client work

Use case 3 – Drafting reports and proposals

Real problem: 38% of each report is repeated from project to project, yet it’s still rewritten manually.
Copy-paste errors mean 1 in every 5 proposals has to be resent.

Approach: AI assembles draft documents from previous reports, templates and CRM data; the consultant only adjusts the analysis and pricing.

  • Measured results:
  • 60% fewer hours spent on mechanical drafting
  • 0 proposals resent due to error
  • 3 days gained in each tender process

Would you like something similar in your consulting firm or practice?

Tell us how you work today and we’ll see whether we can build something similar for your team.

Let’s talk about your case

EDUCATION, ACADEMIES AND TRAINING CONTENT

Use case 1 – Content assistant for students

Real problem: 54% of students drop out before completing 40% of the course because they “can’t find what they need”. Support handles 200 tickets per month, 70% of them repeated.

Approach: a chat assistant connected to videos, PDFs and tests that answers questions and suggests the next learning resource.

  • Measured results:
  • 35% fewer support tickets
  • 18% increase in course completion progress
  • NPS up by 14 points

Use case 2 – Support for tutors and academic staff

Real problem: tutors spend 12 hours per week answering recurring questions (“when does enrolment expire?”, “how do I grade activities?”).

Approach: an internal assistant with all regulations, guides and calendars; when it cannot resolve a query, it opens a ticket already classified.

  • Measured results:
  • 65% fewer repeated emails
  • 9 extra hours per week per tutor freed up for 1-to-1 sessions
  • Job satisfaction up by 22%

Use case 3 – Organising and updating the content base

Real problem: 3,400 duplicated files and 27 versions of the same manual in circulation; no one knows which one is the real source of truth.

Approach: a “prepare your content for AI” project: deduplication, versioning, metadata and an internal RAG system.

  • Measured results:
  • 40% less storage used
  • Content update time: from 3 days to 3 hours
  • Knowledge base ready for new AI projects in 6 weeks

Would you like something similar in your academy?

Tell us how your support and training processes work today and we’ll see if we can design something similar for your team.

Let’s talk about your case

SMEs WITH PRECESSES AND GROWING TEAMS

Use case 1 – Internal help centre for the team

Problem today: the same 3 people answer over 100 times per week the question “how do I onboard a new client?”.

  • Pilot metric:
  • 70% fewer interruptions
  • New-employee onboarding time: from 3 days to 1 day
  • Head of operations recovers 5 hours per week

How we will measure it: “ask the wiki” form with timestamps plus a post-onboarding survey.

Use case 2 – Automating repetitive administrative tasks

Problem today: 800 invoices per month are classified manually; 1 in 20 is entered incorrectly into the ERP, delaying payment.

  • Pilot metric:
  • 90% of invoices auto-classified
  • 0 import errors
  • Days to collect: –5

How we will measure it: automatic reconciliation between ERP and bank statements.

Caso 3 – Soporte a atención al cliente

Problem today: the agent needs 3 minutes to find the warranty policy; the customer leaves the chat before getting an answer.

  • Pilot metric:
  • Response time –50%
  • Customer satisfaction +15%
  • Tickets escalated to a supervisor –30%

How we will measure it: first-response time and post-chat survey.

Would you like something similar in your SME?

Tell us which repetitive tasks are eating up most of your time and we’ll see whether a 4-week pilot makes sense in your case.

Let’s talk about your case