AI partner for small and medium teams

AI transition happens through training

I'm Natalia, I built a company alone in six months using AI. Now I sit with your leadership and business teams and do the same thing inside yours.

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Natalia Morozova

Only 10% of AI's value comes from the algorithms, 20% from the tech implementation, and 70% from rethinking the people side — that is, training

Where teams get stuck

Most common bottlenecks

01

Graveyard of agents

Most teams jump in, spin up a bunch of agents — and six months later, half of them are dead. A graveyard nobody visits. Why: bad output, something broke and nobody fixed it, or the process never should've been automated in the first place.

02

Seemingly easy, but not easy

AI lowered the bar, it didn't remove it. There's still no shortcut up there — you actually have to learn this stuff.

03

Most use cases are generic

The use cases on YouTube are generic on purpose — built to fit everyone, which means they fit no one exactly. Your business and your process have their own quirks, and generic templates don't stretch that far.

04

AI creates new bottlenecks

Spinning up an agent takes five minutes. But most AI agents create new bottlenecks — tool sprawl, review overhead, fragmented processes, maintenance. Teams lose a full workday a week to this. The trick is making AI run smooth — like a carrousel ;)

05

Data is messy

Data is king, knowledge base is close behind. If it's messy, duplicated, outdated, or contradicting itself (happens more than you'd think), your agent has nowhere solid to pull from. Garbage in, garbage out.

06

Overusing or underusing autonomous agents

Most of the time we don't even want to hand over the decision — in those cases, autonomous agents are a terrible idea. Build a smooth human-in-the-loop process instead. But the flip side happens too: teams double-check everything the agent does. A little trust issue. And with zero trust, you save zero time.

07

Unclear responsibility

Who owns this? Who approves a new agent? Who's on the hook when it messes up? Who updates it, who kills it once it's not needed? And if leadership never turns this into a real strategy with real resources behind it... oups.

08

Token burn

AI isn't free, and tokens disappear faster than you'd think. There are ways to burn less — you just have to know them and actually use them.

Who this is for

Small and medium businesses that want to become AI-native.

founders, co-founders, managers

AI for Leadership

AI adoption only spreads if leaders visibly use it themselves. Upgrade your AI and Claude skills and lead by example.

marketing, sales, ops, support, HR

AI for Teams

The best strategy to AI transition is through distributed ownership: each team owns their own AI setup — with a shared layer where what works in one place gets passed to the others. Having one person try to own AI across the whole company "collapses." It doesn't scale as one job.

Choose your format

One-day workshop

Boost

One focused day together, hands-on, on whatever will move the needle most for you or your team.

in person or remote · teams up to 8
€3,500
Two weeks, two hours a day

Immersion

Two weeks gives you room to breathe — try things between sessions, sleep on it, come back with thoughtful questions. That space means we cover more ground, and it actually sticks.

remote · teams up to 10
€7,000
One day a week, six months

Fractional AI Partner

I get to know how your business runs and work alongside your team every week, until using AI becomes how you work. More time, stronger adoption.

remote
€9,000/month

Need something different — a two-day offsite, a different rhythm? Tell me what you're working with and we'll figure out a shape that fits.

Contact

If you remove AI, will your business still function?

The training experience

AI didn't remove the technical barrier. It lowered it enough for you to climb over.

Learning by doing

  • •We sit down and build it together.
  • •You walk away with an upskilled team and an automated process.

Custom training

  • •Built around your actual workflows and business processes.
  • •Some teams need basics, others want to learn to code. We take it from that level and go deeper.

Combo of tech and applied AI skills

  • •The tech side: Claude Cowork and Claude Code, connecting to GitHub, RAG, self-improving agents.
  • •The applied side: Should this be an agent, who's responsible if it breaks, is it actually saving time?

Is your business AI-native, or just AI-assisted?

Five questions and you get a clear picture of where your company stands.

Question 1 of 5

Does your team use ChatGPT or Claude?

Examples of what we can work on

Sessions are tailored to where your team is. Pick the level that fits.

  • Intro to Claude Cowork
  • Identifying repetitive tasks and setting priorities
  • Which processes to convert to an AI agent
  • Autonomous agent, agent with subagent, human in the loop — what's best?
  • Connecting tools
  • Agents, subagents, skills, commands, hooks
  • Token management

These are examples only — the actual concepts will be shaped together at the intro call.

Tell me where you are at

A brief call to see if we are a fit, discuss your needs, and set up a plan.

Book an intro